Careers at Mercor

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together. We have synthetic pipelines and modular quality control systems that run in unison to generate highest quality tasks and at scale. All of it runs on backend systems that have to stay reliable, fast, and observable while the volume behind them grows every month. As a Tech Lead for the Applied AI Backend Systems, you'll own services in that stack: designing the data models, building the APIs, services, Data pipelines that move work through the platform. This is a build role and you'll take a problem that's roughly scoped, ambiguous, make the design calls, ship it to production, and own it afterward, mentor other engineers on the team and grow them. We're hiring for depth in backend fundamentals rather than any particular domain. If you've built and operated real services, handled the schema migration that couldn't take downtime, found the query that fell over at 10x traffic, designed the retry logic that made a flaky dependency invisible to users, or build a system that recover when things break that's the experience that matters here. You'll work with a talent dense group of engineers who will review your designs and push your thinking. What you will Do Own the architecture of the Applied AI backend domain; core services, data models, orchestration systems and the pipeline execution layer that the product and ops team in the org depends on. Set the technical direction, then stay hands-on enough to build the hardest parts yourself. You'll take problems that arrive undefined, decide what's worth building, and own the outcome - the scoping is part of the job, write the design, ship the code, instrument it, and keep it healthy in production. Build and tune high-throughput data and job pipelines: queuing, batching, idempotency, retries, and backpressure. Make the system fast and reliable by adding failure recovery in pipelines, profile hot spots, Agent token and cost attribution, caching issues, and set latency, error, cost budgets you actually hold to. Own the design review bar for backend work across the org. Mentor senior engineers, make the technical tradeoffs legible to leadership in writing, and raise the standard for how we build. Provision and manage infrastructure as code using Terraform and at scale. Manage and launch 10s of 1000s of containers, sandbox environments, manage resource allocation and system health. Participate in on-call for the systems you own, debug production incidents, and write up what you learn in RCCA. Drive XFN alignment across teams through technical judgment and work directly with product, operations, and research partners to turn ambiguous requirements into systems that ship. What we are Looking For 8+ years of professional backend engineering experience building and operating production systems with a track record of owning architecture across multiple teams and of decisions that aged well. Experience mentoring senior engineers, not just junior ones. Strong fundamentals in backend engineering: data structures, algorithms, concurrency, and writing code that's clear enough for the next person to change. Hands-on experience with API design - REST, gRPC, or GraphQL, and an understanding of versioning, contracts, and backward compatibility. Solid database skills : relational data modeling, indexing, query performance, transactions and isolation, and safe migrations. Familiarity with at least one NoSQL or key-value store and when it's the right choice. Deep, hands-on expertise in distributed systems : queues and event streams, caching, idempotency, rate limiting, and designing for partial failure. Experience with Data Orchestration and workflow management systems like Airflow, Temporal, Dagster. Be able to roll your sleeves up and dig deeper into the lower level infrastructure issues container, permissions, logs, traces and find the needle in the haystack. Experience running services in production: containers, CI/CD, monitoring and alerting, and debugging issues under real traffic. Comfort with ambiguity you can take a loosely defined problem, ask the right questions, and come back with a plan. Strong opinions, loosely held. Genuine excitement for agentic development and new technology, fluency with modern AI dev tools (e.g. Claude Code, Cursor, Copilot), and a real passion for writing good code. Clear written and verbal communication. High ownership, pragmatism, and a bias toward shipping. Nice to Have Experience building or integrating with LLM-backed services in production (evaluation, orchestration, or serving). Familiarity with AI infrastructure providers like Modal, Fireworks, Baseten, Temporal Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together. We have synthetic pipelines and modular quality control systems that run in unison to generate highest quality tasks and at scale. All of it runs on backend systems that have to stay correct, fast, and observable while the volume behind them grows every month. As a Software Engineer on Backend Systems, you'll own services in that stack: designing the data models, building the APIs, services, data pipelines that move work through the platform. This is a build role. You'll take a problem that's roughly scoped, make the design calls, ship it to production, and own it afterward. We're hiring for depth in backend fundamentals rather than any particular domain. If you've built and operated real services, handled the schema migration that couldn't take downtime, found the query that fell over at 10x traffic, designed the retry logic that made a flaky dependency invisible to users, or build a system that recover when things break that's the experience that matters here. You'll work with a talent dense group of engineers who will review your designs and push your thinking, and you'll be expected to grow into owning larger surfaces quickly. What you will Do Design, build, and operate backend services in the Applied AI stack including APIs, data models, background jobs, and the pipelines that connect them. Own features end to end: scope the problem, write the design, ship the code, instrument it, and keep it healthy in production. Build and tune high-throughput data and job pipelines: queuing, batching, idempotency, retries, and backpressure. Make the system fast and reliable by adding failure recovery in pipelines, profile hot spots, Agent token and cost attribution, caching issues, and set latency, error, cost budgets you actually hold to. Instrument what you ship: observability, metrics, logging, tracing, and alerts that proactively catch problems. Work on modern cutting edge tools, libraries and frameworks. Manage and launch 10s of 1000s of containers, sandbox environments, manage resource allocation and system health. Manage infrastructure as code using Terraform. Participate in on-call for the systems you own, debug production incidents, and write up what you learn in RCCA. Write clear design docs and give useful code review, we make technical decisions in writing and expect everyone to take part. Work directly with product, operations, and research partners to turn ambiguous requirements into systems that ship. What we are Looking For 2–5 years of professional backend engineering experience building and operating production systems. Strong fundamentals in backend engineering: data structures, algorithms, concurrency, and writing code that's clear enough for the next person to change. Hands-on experience with API design - REST, gRPC, or GraphQL, and an understanding of versioning, contracts, and backward compatibility. Solid database skills : relational data modeling, indexing, query performance, transactions and isolation, and safe migrations. Familiarity with at least one NoSQL or key-value store and when it's the right choice. Practical experience with distributed systems basics : queues and event streams, caching, idempotency, rate limiting, and designing for partial failure. Experience with Data Orchestration and workflow management systems like Airflow, Temporal, Dagster. Be able to roll your sleeves up and dig deeper into the lower level infrastructure issues container, permissions, logs, traces and find the needle in the haystack. Experience running services in production: containers, CI/CD, monitoring and alerting, and debugging issues under real traffic. Comfort with ambiguity you can take a loosely defined problem, ask the right questions, and come back with a plan. Genuine excitement for agentic development and new technology, fluency with modern AI dev tools (e.g. Claude Code, Cursor, Copilot), and a real passion for writing good code. Clear written and verbal communication. High ownership, pragmatism, and a bias toward shipping. Nice to Have Experience building or integrating with LLM-backed services in production (evaluation, orchestration, or serving). Familiarity with AI infrastructure providers like Modal, Fireworks, Baseten, Temporal Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role Frontier AI is going physical, and the labs building it are bottlenecked on one thing: high-quality data from the real world. Mercor pairs its operational scale with the specialized engineering that physical-world data demands. As a Software Engineer on Robotics, you'll sit between Mercor's data systems and our customers' infrastructure. Every frontier lab wants something different: container format, schema, fields, and quality requirements. You'll build infrastructure general enough that a new customer becomes a quick configuration, and you'll work directly with customer engineering teams on bespoke requests, feeding what you learn into scalable platform architecture decisions. An example might be modifying the segmentation model derived from a customer request for stricter filtering on hands being in frame and building this into a configurable pipeline feature. Prior robotics experience is not required. This is a backend and data engineering role at its core, developing pipelines, formats, and storage methods. If you've built high-volume data infrastructure anywhere and want depth in robotics data and directly, working directly with the engineers and researchers at the labs and robotics companies building physical AI, this role is for you. What You'll Do Own the reusable infrastructure behind robotics data deliveries: the processing, packaging, and delivery systems Format and transform datasets to per-client specification: MCAP and other container formats, custom schemas, field mappings, metadata, and versioning Work directly with customer engineering teams to scope and build bespoke schemas, custom fields, and one-off transforms where requirements are custom Build and operate the pipelines that move data from Mercor's systems into customer storage reliably at petabyte scale Partner with operations and product to turn evolving requirements into shipped data deliveries, and prototype quickly when a new data type or customer arrives Build automated validation techniques What We're Looking For Strong backend and data engineering fundamentals in a modern language (Python, Go, Rust) and comfort operating production systems on AWS and GCP Experience building and owning high-volume data pipelines, not just contributing to them Experience with large binary formats, streaming ingestion, distributed batch processing, and object storage economics Customer-facing instincts: you can lead a technical conversation, ask the right questions, and push back when a request is unreasonable Comfort working through ambiguity and shipping iteratively with a product team, where requirements evolve with the customers and data types Nice to Have Experience with robotics/AV data formats and tooling such as MCAP, ROS, protobuf, Foxglove Prior work on data engines, pipelines, or delivery for multimodal data Multi-sensor data experience across video, depth, inertial, and audio, including calibration and synchronization Forward-deployed, solutions, or delivery engineering experience at a data or infrastructure company Computer vision or multimodal ML exposure: detection, tracking, or VLM-based labeling and QC Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. What This Person Owns The infrastructure every data-driven team at Mercor runs on: Snowflake, Fivetran, Airflow, and Hex. You own how data is organized, who can access what, what it costs to run, and how reliably it operates. This is a foundational hire on a new Data Platform team, you'll help set the standards other engineers build against. What They Do Day-to-Day - Bring structure and clear ownership to how data is organized in Snowflake across projects and teams - Design narrow, role-based access controls, and partner with automation so access is granted and revoked as people join, change teams, or leave - Extend row access policies and PII masking across all sensitive datasets - Migrate data from a variety of vendor and internal sources into properly owned, governed homes - Own Fivetran connector health and cost, Airflow/Astronomer pipeline reliability and on-call, and Hex governance across company-wide dashboards - Monitor and right-size Snowflake warehouse spend - Help build CDC/streaming ingestion and other internal data platform tooling What We're Looking For - Hands-on experience with Snowflake administration: roles, grants, warehouses, cost/performance tuning - Experience designing data access and governance models (RBAC, row-level security, PII) at scale - Comfort owning vendor tooling end to end (Fivetran, Airflow/Astronomer, or similar), including on-call - Track record migrating or re-architecting live production data systems without breaking dependent teams - Strong SQL and Python, with infrastructure fluency to make judgment calls, not just execute a spec - Experience owning CDC/streaming pipelines in production (Debezium, Kafka, Snowpipe Streaming or similar), including reasoning about delivery semantics, partitioning, and safe cutovers between systems. Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role Frontier models increasingly depend on data that goes beyond text: images, video, audio, documents, and combinations of these modalities. Turning that raw material into useful data products is technically difficult. Each modality has different formats, quality failures, processing costs, privacy considerations, and review workflows. The final product still needs to be consistent, traceable, and trustworthy. Mercor’s Frontier Data Products team builds the systems that make these products possible. As Tech Lead Manager, you will lead the team responsible for turning complex multimodal inputs into reliable, customer-ready data products at scale. This is a player-coach role, split roughly evenly between technical contribution and people leadership. You will write and review production code, own important architecture decisions, and help resolve the hardest production problems. You will also hire, coach, and organize a team that can operate with clear ownership and strong independent judgment. This is a product-engineering leadership role. Applied ML is part of the system, but success is measured by the quality, reliability, and usefulness of the products delivered—not by research output alone What You’ll Do Set the technical and product strategy for Mercor’s multimodal data products. Design systems that support the full lifecycle of image, video, audio, document, and mixed-media data—from initial inputs through processing, review, validation, versioning, and delivery. Create reusable abstractions across modalities while preserving the differences that matter for quality, performance, and customer requirements. Build quality systems that combine automated evaluation, model-assisted checks, expert review, sampling, and adjudication. Ensure that every output is traceable: what produced it, what changed, how it was evaluated, and why it was accepted. Own the reliability, performance, and cost of storage-heavy, compute-intensive, long-running workflows. Stay hands-on by writing production code, leading design reviews, and directly contributing to the team’s most consequential technical work. Manage and develop engineers through clear expectations, frequent feedback, thoughtful delegation, and meaningful ownership. Partner with product, ML, operations, and customer-facing teams to turn new customer needs into durable product capabilities rather than one-off solutions. Recruit and onboard engineers who raise the team’s technical and execution bar. What Makes This Role Different You will shape both the multimodal product architecture and the engineering team building it. The technical challenge extends beyond moving large media files. The system must preserve context, relationships, provenance, and quality across different modalities and transformations. Customer requirements and available models will evolve quickly. The architecture must support new products without requiring the team to rebuild the system for every use case. The team’s work sits directly between complex real-world inputs and the data products delivered to frontier AI customers. What Success Looks Like The team can launch support for a new modality or product without building an entirely separate system. Product quality is measurable, explainable, and auditable across human and model-assisted workflows. Large, long-running jobs are observable and recoverable, with failures detected before they affect customer deliveries. Customer-specific work produces reusable capabilities that make the next product faster to build. - Engineers own substantial areas independently rather than depending on the manager for every technical decision. The team improves delivery speed while maintaining clear standards for quality, reliability, privacy, and cost. What We Are Looking For Experience managing a strong engineering team while remaining an effective, hands-on technical leader. Deep experience designing and operating production backend, distributed, or data-intensive systems. Experience working with large unstructured data, asynchronous processing, metadata and versioning, or compute-heavy workflows. Relevant experience in at least one area such as multimedia infrastructure, computer-vision data, video or audio processing, ML platforms, annotation systems, or human-in-the-loop products. Strong judgment about platform boundaries: what should be generalized across modalities and what should remain modality-specific. A track record of taking ambiguous, zero-to-one products through architecture, launch, and sustained production operation. Evidence that you can recruit, coach, and retain excellent engineers while maintaining a high performance bar. Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role As an Infrastructure Engineer at Mercor, you’ll build and scale the systems that power our rapid growth. You’ll ensure our infrastructure is highly available, cost-effective, and able to handle explosive traffic and compute demands. You’ll work closely with engineers across product, research, and operations to design scalable architectures, streamline deployments, and improve observability. This is a software engineering role. You'll spend most of your time designing and writing the services, platforms, and tooling that the rest of engineering builds on, and the rest making sure they hold up in production. We're hiring across Infrastructure: Platform, Developer Productivity, Production Engineering, Storage and Databases. We team-match after the first screen, so apply even if your background leans toward one area. What You'll Work On Design and build the platforms that sit between our engineers and the outside world: multi-tenant services that give dozens of teams isolated capacity, routing, quotas, and observability on demand, owned from architecture review through production. Build the internal platforms and solutions that product and research engineers rely on every day, from deploy tooling to on-call automation, and treat them with the same design and testing rigor as customer-facing code. Scale our multi-tenant services that fronts every model provider we use, so dozens of internal teams and products get isolated quotas, routing, observability, and capacity on demand without filing a ticket. Run Temporal, Postgres, MongoDB, and our Kubernetes fleet at a scale where "it worked last month" isn't a guarantee, and design for the next 10x. Own the reliability program: define SLOs that matter, kill noisy alerts, make CI/CD deploys boring, and turn every incident into a durable fix rather than a runbook entry. Build the developer platform for an engineering org that ships dozens of times a day, and where coding agents are now first-class users of our CI, sandboxes, and deploy pipelines. Design network and identity boundaries across production, preprod, and research compute so teams move fast without cross-environment risk. Make the cost picture legible: attribute spend across data centers, and inference providers, and find the architectural changes that bend the curve. Build the tooling that lets the rest of engineering self-serve: our on-call is already AI-triaged and auto-assigned; you'll decide what gets automated next. What We're Looking For We care far more about how you reason about systems than which tools you've used. Strong candidates typically have: A deep grasp of reliability and scalability fundamentals: failure modes, backpressure, idempotency, capacity planning, and how distributed systems actually break under load. Experience operating production systems that real users depend on, and the scars to prove it. Strong software engineering fundamentals: you design systems before you build them, write code you're proud of in Python or Go, test it, and review others' code with care. Most of your recent work has been shipping software, not clicking through consoles. Familiarity with cloud infrastructure (we're on AWS) and infrastructure-as-code (we use Terraform). You don't need to be an expert; you need to be curious and fast to pick it up. Working knowledge of containers and how they're deployed. Kubernetes experience is a plus, not a gate. High ownership: you see a gap, you write the proposal, you ship it, you carry the pager for it. You Might Be a Great Fit If You're a backend engineer with strong infra fundamentals who keeps getting pulled toward the platform layer because that's where the hardest problems are. You've been the person who understood why the system fell over when nobody else did. You've built internal platforms or tooling that other engineers loved using. You've operated databases, message queues, or workflow engines at meaningful scale. You've come from backend or DevOps and want to own infrastructure end to end. How We Work Small, senior team with direct access to the head of infra and to engineering leadership. In-person five days a week in SF, or NYC. Infra is a team sport for us. We use AI coding agents heavily and expect you to as well; the interesting work is deciding what they should do, not typing. Weekly on-call rotation with structured handoffs; on-call load is a metric we actively drive down. Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role As an Infrastructure Engineer at Mercor, you’ll build and scale the systems that power our rapid growth. You’ll ensure our infrastructure is highly available, cost-effective, and able to handle explosive traffic and compute demands. You’ll work closely with engineers across product, research, and operations to design scalable architectures, streamline deployments, and improve observability. This is a software engineering role. You'll spend most of your time designing and writing the services, platforms, and tooling that the rest of engineering builds on, and the rest making sure they hold up in production. We're hiring across Infrastructure: Platform, Developer Productivity, Production Engineering, Storage and Databases. We team-match after the first screen, so apply even if your background leans toward one area. What You'll Work On Design and build the platforms that sit between our engineers and the outside world: multi-tenant services that give dozens of teams isolated capacity, routing, quotas, and observability on demand, owned from architecture review through production. Build the internal platforms and solutions that product and research engineers rely on every day, from deploy tooling to on-call automation, and treat them with the same design and testing rigor as customer-facing code. Scale our multi-tenant services that fronts every model provider we use, so dozens of internal teams and products get isolated quotas, routing, observability, and capacity on demand without filing a ticket. Run Temporal, Postgres, MongoDB, and our Kubernetes fleet at a scale where "it worked last month" isn't a guarantee, and design for the next 10x. Own the reliability program: define SLOs that matter, kill noisy alerts, make CI/CD deploys boring, and turn every incident into a durable fix rather than a runbook entry. Build the developer platform for an engineering org that ships dozens of times a day, and where coding agents are now first-class users of our CI, sandboxes, and deploy pipelines. Design network and identity boundaries across production, preprod, and research compute so teams move fast without cross-environment risk. Make the cost picture legible: attribute spend across data centers, and inference providers, and find the architectural changes that bend the curve. Build the tooling that lets the rest of engineering self-serve: our on-call is already AI-triaged and auto-assigned; you'll decide what gets automated next. What We're Looking For We care far more about how you reason about systems than which tools you've used. Strong candidates typically have: A deep grasp of reliability and scalability fundamentals: failure modes, backpressure, idempotency, capacity planning, and how distributed systems actually break under load. Experience operating production systems that real users depend on, and the scars to prove it. Strong software engineering fundamentals: you design systems before you build them, write code you're proud of in Python or Go, test it, and review others' code with care. Most of your recent work has been shipping software, not clicking through consoles. Familiarity with cloud infrastructure (we're on AWS) and infrastructure-as-code (we use Terraform). You don't need to be an expert; you need to be curious and fast to pick it up. Working knowledge of containers and how they're deployed. Kubernetes experience is a plus, not a gate. High ownership: you see a gap, you write the proposal, you ship it, you carry the pager for it. You Might Be a Great Fit If You're a backend engineer with strong infra fundamentals who keeps getting pulled toward the platform layer because that's where the hardest problems are. You've been the person who understood why the system fell over when nobody else did. You've built internal platforms or tooling that other engineers loved using. You've operated databases, message queues, or workflow engines at meaningful scale. You've come from backend or DevOps and want to own infrastructure end to end. How We Work Small, senior team with direct access to the head of infra and to engineering leadership. In-person five days a week in SF, or NYC. Infra is a team sport for us. We use AI coding agents heavily and expect you to as well; the interesting work is deciding what they should do, not typing. Weekly on-call rotation with structured handoffs; on-call load is a metric we actively drive down. Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. You'll own application security at a company where the app layer is the highest-priority security surface. This is not a scan-and-triage role. You'll embed in the development lifecycle, review code for exploitable flaws, build security tooling into CI/CD, and drive vulnerability remediation across a platform serving 300K+ experts and enterprise clients processing sensitive AI training data. We use AI heavily in our own security work. You should be comfortable building alongside AI code-gen tools, using LLMs to accelerate code review and threat modeling, and automating away the repetitive work that slows AppSec programs down. If you'd rather write a CodeQL query than file a Jira ticket, you'll fit in here. We're in-person five days a week at our SF headquarters, with first Fridays remote. What You'll Build: Security review workflows embedded in the SDLC - PR-level analysis that catches auth bugs, injection flaws, and business logic errors before they ship SAST/DAST pipelines integrated into CI/CD - shifting security left without slowing down deploys Vulnerability management processes that prioritize by real exploitability, not CVSS score Secure coding standards and guardrails that make the safe path the easy path for 50+ engineers Threat models for new features and architecture changes - especially around AI data pipelines, payment flows, and multi-tenant boundaries Bug bounty program operations - triaging HackerOne reports, validating findings, and driving fixes to closure What We're Looking For You've found and fixed real vulnerabilities in production applications - not just run scanners Deep understanding of web application security: OWASP Top 10 is baseline, you think in terms of attack chains and business logic flaws Strong in at least one of Python, TypeScript, or Go - you can read a PR and spot the auth bypass Experience building or tuning SAST/DAST tooling (Semgrep, CodeQL, Snyk, Burp, or similar) You understand modern web frameworks, APIs, and authentication patterns well enough to threat model them Experience managing a vulnerability pipeline - from discovery through prioritization to verified remediation 5+ years of professional experience in application security, security engineering, or software engineering with a strong security focus Bonus Points Experience running or triaging a bug bounty program (HackerOne, Bugcrowd) Offensive security skills - you've done penetration testing and can think like an attacker Experience securing AI/ML applications - model serving APIs, training data pipelines, prompt injection defense Familiarity with supply chain security - dependency scanning, registry firewalls (Socket, Snyk) You've built custom security tooling that a team still uses Contributions to open source security projects or published vulnerability research Why Mercor The problem is real. Application security at scale is hard - you'll build defenses that matter across a fast-moving platform. AI-native AppSec. You'll use frontier AI tools daily - for code review, vulnerability analysis, and anything that benefits from an AI co-pilot. Ownership from day one. You'll own the entire application security domain - from code review processes to CI/CD security to bug bounty operations. See the future early. Working alongside AI labs means you'll understand frontier model capabilities months before the market. Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. You'll own application security at a company where the app layer is the highest-priority security surface. This is not a scan-and-triage role. You'll embed in the development lifecycle, review code for exploitable flaws, build security tooling into CI/CD, and drive vulnerability remediation across a platform serving 300K+ experts and enterprise clients processing sensitive AI training data. We use AI heavily in our own security work. You should be comfortable building alongside AI code-gen tools, using LLMs to accelerate code review and threat modeling, and automating away the repetitive work that slows AppSec programs down. If you'd rather write a CodeQL query than file a Jira ticket, you'll fit in here. We're in-person five days a week at our SF headquarters, with first Fridays remote. What You'll Build: Security review workflows embedded in the SDLC - PR-level analysis that catches auth bugs, injection flaws, and business logic errors before they ship SAST/DAST pipelines integrated into CI/CD - shifting security left without slowing down deploys Vulnerability management processes that prioritize by real exploitability, not CVSS score Secure coding standards and guardrails that make the safe path the easy path for 50+ engineers Threat models for new features and architecture changes - especially around AI data pipelines, payment flows, and multi-tenant boundaries Bug bounty program operations - triaging HackerOne reports, validating findings, and driving fixes to closure What We're Looking For You've found and fixed real vulnerabilities in production applications - not just run scanners Deep understanding of web application security: OWASP Top 10 is baseline, you think in terms of attack chains and business logic flaws Strong in at least one of Python, TypeScript, or Go - you can read a PR and spot the auth bypass Experience building or tuning SAST/DAST tooling (Semgrep, CodeQL, Snyk, Burp, or similar) You understand modern web frameworks, APIs, and authentication patterns well enough to threat model them Experience managing a vulnerability pipeline - from discovery through prioritization to verified remediation 5+ years of professional experience in application security, security engineering, or software engineering with a strong security focus Bonus Points Experience running or triaging a bug bounty program (HackerOne, Bugcrowd) Offensive security skills - you've done penetration testing and can think like an attacker Experience securing AI/ML applications - model serving APIs, training data pipelines, prompt injection defense Familiarity with supply chain security - dependency scanning, registry firewalls (Socket, Snyk) You've built custom security tooling that a team still uses Contributions to open source security projects or published vulnerability research Why Mercor The problem is real. Application security at scale is hard - you'll build defenses that matter across a fast-moving platform. AI-native AppSec. You'll use frontier AI tools daily - for code review, vulnerability analysis, and anything that benefits from an AI co-pilot. Ownership from day one. You'll own the entire application security domain - from code review processes to CI/CD security to bug bounty operations. See the future early. Working alongside AI labs means you'll understand frontier model capabilities months before the market. Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. The Role We're looking for a Cloud Platform Engineer to own the internal IT infrastructure Mercor runs on — and to run it as code. You'll design and operate the platform layer beneath our identity, cloud, and SaaS systems: Okta configuration managed in Terraform, cloud IAM and account structure defined declaratively, and employee lifecycle provisioning automated end to end. You'll also own identity planning as we scale from hundreds to thousands of employees. This role reports directly to the Head of IT and is critical to our operational foundation. What You'll Do Own Mercor's identity infrastructure — Okta configuration and provisioning — managed as code in Terraform rather than clicked through a console Design and implement SCIM integrations across our SaaS stack, automating user provisioning and deprovisioning Own identity planning and architecture as we scale: access models, group strategy, and how entitlements evolve from hundreds to thousands of employees Own cloud account structure, IAM roles, and permission boundaries across AWS, GCP, Azure, and Vercel, keeping access least-privilege as the org grows Build and maintain Terraform for internal platforms so environments are reproducible and every change is reviewable Build automation that cuts manual ticket volume for employee onboarding and offboarding Design and own secrets management, key rotation, and service-account lifecycle Troubleshoot identity and infrastructure issues, trace root causes, and implement systemic fixes Document platform architecture, runbooks, and automation so the team can operate and extend it Mentor future IT team members on infrastructure-as-code, automation practices, and systems thinking Help establish sustainable escalation procedures as the team grows You may be a good fit if you have: Hands-on production experience with Terraform, managing real infrastructure as code Production experience with Okta and SCIM integrations — ideally managed declaratively Strong skills with IAM roles and permissions across at least two major cloud platforms — AWS, GCP, or Azure — with Vercel a plus Proficiency in at least one programming language with demonstrated understanding of core coding principles Experience building automated workflows across systems via APIs Strong incident management skills: triage, root-cause analysis, and systems thinking Strong documentation skills — able to write technical guides other team members can follow and learn from Clear communication skills — able to explain technical identity and infrastructure concepts to non-technical stakeholders A systems-thinking mindset that naturally traces dependencies and considers second-order effects Location and Commitment San Francisco, CA. Full-time, five days a week in office. This role participates in an on-call rotation for weekend emergencies.