Careers at Axios

1 big thing: Axios is a growth-focused media company helping people get smarter, faster, on what matters. We’re looking for a Staff Software Engineer—a senior, hands-on individual contributor—to lead architecture and delivery for Axios’ core products across multiple teams using strong product-engineering and AI-native practices. Why it matters: Axios delivers clear, trustworthy news to millions of readers. You’ll be anchored to a product area while shaping full-stack systems and technical direction across multiple teams and connected systems. This is not a people-management role. AI is core to how we build. You’ll use coding agents throughout implementation, testing, review, debugging, documentation, and operations while remaining accountable for architecture, quality, security, and product outcomes. Staff impact comes from sustained scope, judgment, and results—not tool use alone. You’ll work with product managers, designers, engineers, and leaders to shape plans, align dependencies, resolve ambiguity, build resilient systems, and help others make better technical decisions. Responsibilities: As a Staff Software Engineer, you’ll lead reliable product and platform work across Axios’ frontend and backend systems. You’ll remain hands-on while driving multi-quarter initiatives, improving technical coherence, and using agentic practices to accelerate delivery. Key responsibilities include: Cross-team technical leadership: Lead mission-critical or high-risk initiatives spanning teams and connected systems. Frame problems, align ownership and dependencies, make tradeoffs explicit, and drive production adoption. Architecture and design: Own architecture for a product area and scalable boundaries across frontend, APIs, data, and production systems. Lead design reviews and establish standards within your sphere of influence. Hands-on system ownership: Own the technical direction and long-term evolution of key systems while writing and reviewing code, prototyping, debugging, leading migrations, and operating services in production. AI-enabled product and engineering: Identify where models, agents, retrieval, or automation create value. Build reusable capabilities with measurable behavior, guardrails, and judgment about when conventional software is better. Quality, reliability, and incident leadership: Improve testing, performance, observability, security, and operational readiness. Anticipate systemic risks, address technical debt, and help lead resolution and learning during critical production issues. Technical leadership and mentorship: Mentor mid- and senior-level engineers across teams, spread systems thinking and design patterns, and build alignment through proposals, reviews, and influence without authority. Product and technical strategy: Partner with product, design, and engineering leaders to shape the product-area roadmap, align dependencies, and connect technical investment to reader, editorial, and business outcomes. Skills: The ideal candidate is a staff-level engineer with sustained multi-team impact, deep expertise in a relevant domain, broad systems thinking, and a commitment to user experience, reliability, scalability, maintainable code, and effective AI-enabled practice. You should have: Experience: Typically 7+ years in professional software development, or equivalent sustained Staff-level impact, including leading complex initiatives across multiple teams or systems. AI-native development: Hands-on experience using agentic coding tools—such as Claude Code, Codex, Cursor, GitHub Copilot, or comparable tools—to complete meaningful, multi-step software work, rather than only generating snippets or using autocomplete. Agent direction and context: Ability to write clear strategies, specifications, and acceptance criteria; provide context; scope complex work; decide what to delegate; and redirect incomplete or incorrect approaches. Verification and engineering judgment: Ability to review AI-generated code critically, validate assumptions, identify security, scalability, and maintainability risks, and catch plausible but wrong solutions. You understand that AI raises the importance of sound architecture, testing, and human judgment. Frontend development: Hands-on experience building production interfaces with JavaScript or TypeScript and React, preferably with Next.js, plus judgment to guide frontend architecture across teams. Backend development: Hands-on experience building production services and APIs. Our backend systems use Go and Python, and you should be able to shape reliable service boundaries and work effectively in or learn either language. Data fundamentals: Experience with relational databases, SQL, schema design, transactions, and migrations. Quality and security: Experience with testing, accessibility, input validation, authentication, authorization, and web security practices, plus the ability to raise standards across teams. Engineering judgment: Ability to operate independently in ambiguity, identify high-leverage problems, align teams, make sound tradeoffs, and connect decisions to product and business goals—including when AI is not the right tool. Communication: Ability to build alignment through clear proposals and reasoning, communicate risks and tradeoffs across functions, and drive clarity during disagreement. Continuous learning: Curiosity about changing models, tools, and practices, paired with an evidence-based approach. You share useful patterns, identify what fails, and make others more effective. We’ll be even more excited if you have: Experience building production AI-enabled features using model APIs, structured outputs, tool or function calling, retrieval, or agent workflows. Experience evaluating and operating AI-enabled systems through regression tests, evaluation harnesses, tracing, feedback loops, model or prompt versioning, cost and latency monitoring, or human-review paths. Experience extending AI development environments through MCP servers, agent tools, repository instructions, reusable skills or plugins, custom workflows, or automated code review. Led a multi-team architecture, platform, migration, or modernization initiative from problem framing through production adoption. Owned critical systems through incidents, scaling challenges, and long-term architectural evolution. Drove adoption of technical standards, reusable tools, or platform capabilities across multiple teams. Mentored experienced engineers and helped improve technical judgment beyond your immediate team. Experience with CMS, publishing, media, subscription, search, or other consumer-facing products. Production experience with Go or Python and distributed systems using gRPC, cloud infrastructure, containers, queues, CI/CD, or similar technologies. What success looks like: Cross-team delivery: You drive multi-quarter initiatives from problem framing through production adoption, aligning dependencies and ownership to produce durable outcomes. Engineering leverage: Teams deliver more effectively because of the standards, tools, architecture, documentation, and context you create. You establish safe, repeatable AI patterns where they add value. System health: Key systems become more reliable, scalable, secure, observable, and easier to change. You reduce systemic risk and improve incident prevention and response. Product-area impact: Your decisions support Axios’ readers, products, editorial workflows, and business goals within the teams and systems you influence. Organizational technical leadership: Engineers across teams make better decisions through your mentorship, proposals, reviews, and example. You remain a hands-on IC who multiplies others’ effectiveness. Starting salary for this role is in the range of $165,000 - $215,000 and is dependent on numerous factors, including but not limited to location, work experience, and skills. This range does not include other compensation benefits. Axios' compensation philosophy takes into account the cost of labor differentials across the country. Because this is a remote-optional job posting, this salary range takes into account all possible locations within the United States, but candidates will only be eligible for the salary range for their location. Axios is committed to embracing artificial intelligence as a core part of how we work. All team members are expected to actively develop AI literacy and use AI tools to enhance their productivity, creativity, and efficiency. We invest in ongoing learning to ensure every employee is equipped to responsibly and effectively integrate AI into their daily workflows. What Axios brings to the table besides salary: 401(k) with employer match Robust PPO and High Deductible health insurance options on the Blue Cross Blue Shield network Employer Health Savings Account (HSA) contribution for the high deductible health plan option Dental and vision coverage Primary caregiver 12-week paid leave Birth-givers will have an additional 6-8 weeks depending on type of delivery, for a total of 18-20 weeks continuous leave Generous vacation policy, plus holidays One mental health day per quarter Annual learning and development stipend $100 monthly work-from-home stipend Tele-mental health services through Headspace OneMedical membership, including tele-health services Personal health advocacy resources through HealthAdvocate Inclusive fertility, hormonal health and family forming benefits through Carrot Fertility Access to the Axios “Family Fund”, which was created to allow employees to request financial support when facing financial hardship or emergencies Increased work flexibility for parents and caretakers Virtual company-sponsored social events A strong and positive work environment A commitment to an open, inclusive, and diverse work culture Equal Opportunity Employer Statement Axios is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, age, gender identity, gender expression, veteran status, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Axios makes hiring decisions based solely on qualifications, merit, and business needs at the time.

1 big thing: Axios is a growth-focused media company dedicated to helping people get smarter, faster, on what matters. We’re looking for a Full Stack Software Engineer who pairs strong product-engineering fundamentals with modern AI-native development practices to build and scale the systems and experiences that power Axios’ core products. Why it matters: At Axios, we deliver clear, trustworthy, and informative news to millions of readers every day. As a Full Stack Software Engineer , you’ll build the interfaces, services, APIs, and data flows behind our audience-facing products and publishing tools. AI has become a core part of how we build software. You’ll use coding agents and other AI tools throughout the development lifecycle—from understanding problems and exploring solutions through implementation, testing, review, debugging, documentation, and operation. You’ll remain accountable for the architecture, quality, security, and product outcomes of everything you ship. You’ll work with product managers, designers, and engineers across disciplines to build resilient systems that embody Axios’ commitment to clarity and make our readers smarter. Responsibilities: As a Full Stack Software Engineer, you’ll deliver high-quality, reliable product features across Axios’ frontend and backend systems, using modern agentic development practices to accelerate delivery and ensuring performance and stability across our publishing and delivery platforms. Key responsibilities include: End-to-end feature development: Own features across the frontend, APIs, business logic, data layer, testing, and production systems. Turn product problems into clear technical plans and reviewable units of work, using AI agents thoughtfully across research, prototyping, implementation, testing, refactoring, and documentation. Frontend development: Create accessible, responsive, and maintainable interfaces using JavaScript or TypeScript, React, and modern web frameworks such as Next.js. Backend and API development: Build production services and APIs that support Axios’ products and publishing workflows, and create clear contracts that can be understood and used reliably by people, applications, and AI-powered tools. AI-enabled product development: Identify opportunities where models, agents, retrieval, or intelligent automation can create meaningful value for readers or internal teams. Build those capabilities with clear user controls, measurable behavior, appropriate guardrails, and an understanding of when conventional software is the better solution. Quality and reliability: Write automated tests, improve performance, and contribute to logging, metrics, tracing, security, and operational reliability. Collaboration: Partner with product, design, quality engineering, and other developers to clarify requirements, explain tradeoffs, and deliver effectively. Participate in code reviews, pairing, onboarding, and mentorship. Product and technical improvement: Understand how technical work supports readers, editorial workflows, and business goals.Improve existing systems through thoughtful refactoring, sound technical decisions, and practical experimentation with emerging engineering approaches. Skills: The ideal candidate is a thoughtful engineer who cares about user experience, reliability, scalability, and maintainable code—and who has moved beyond occasional AI assistance to using agents as a substantive part of their engineering practice. You should have: Experience: 2-5+ years of professional software development experience, with production experience in frontend, backend, or full-stack development and the ability to contribute across the stack. AI-native development: Hands-on experience using agentic coding tools—such as Claude Code, Codex, Cursor, GitHub Copilot, or comparable tools—to complete meaningful, multi-step software work, rather than only generating snippets or using autocomplete. Agent direction and context: Ability to write clear specifications and acceptance criteria, provide relevant context, break work into appropriately scoped tasks, decide what to delegate, and guide an agent when its initial approach is incomplete or incorrect. Verification and engineering judgment: Ability to review AI-generated code critically, validate assumptions against the actual system, identify security and maintainability risks, and recognize when an agent-produced solution is plausible but wrong. You understand that AI increases the importance of sound architecture, testing, and human judgment. Frontend development: Experience building production interfaces with JavaScript or TypeScript and React, preferably with Next.js or a comparable modern framework. Backend development: Experience building production services and APIs. Our backend systems primarily use Go and Python, and you should be comfortable working in or learning either language. Data fundamentals: Experience with relational databases, SQL, schema design, transactions, and migrations. Quality and security: Experience with unit and integration testing, accessibility, input validation, authentication, authorization, and common web security practices. Engineering judgment: Ability to own scoped work, make sound tradeoffs, navigate ambiguity, and connect technical decisions to product and business goals. You can evaluate when an AI-assisted or AI-enabled approach creates real leverage and when a straightforward deterministic solution is more appropriate. Communication: Ability to explain technical decisions, risks, blockers, and tradeoffs clearly to engineering and cross-functional partners. Continuous learning: Curiosity about rapidly changing models, tools, and development practices, paired with an evidence-based approach to evaluating them. You share what works, identify what does not, and help the team improve its practices over time. We’ll be even more excited if you have: Experience building production AI-enabled features using model APIs, structured outputs, tool or function calling, retrieval, or agent workflows. Experience evaluating and operating AI-enabled systems through regression tests, evaluation harnesses, tracing, feedback loops, model or prompt versioning, cost and latency monitoring, or human-review paths. Experience extending AI development environments through MCP servers, agent tools, repository instructions, reusable skills or plugins, custom workflows, or automated code review. Production experience with Go or Python. Experience with gRPC, Protocol Buffers, generated clients, or service-oriented architectures. Experience with cloud infrastructure, containers, orchestration, or CI/CD. Experience with caching, background jobs, queues, or asynchronous processing. Experience with CMS, publishing, media, subscription, search, or other consumer-facing products. Experience operating production systems with observability, performance optimization or benchmarking, or accessibility testing. What success looks like: Valuable, accelerated delivery: You ship useful features from concept through production and use AI to shorten research, implementation, and feedback cycles without creating avoidable rework. Sound AI leverage: You delegate meaningful work to agents, give them the context and constraints needed to succeed, and verify their output before it reaches users. You know when AI adds value and when it introduces unnecessary complexity. Quality and reliability: Your work is maintainable, well-tested, secure, accessible, observable, and dependable. Product impact: You make technical decisions that support Axios’ readers, products, editorial workflows, and business goals. Team and system improvement: You contribute to a stronger team through collaboration, code reviews, pairing, mentorship, and thoughtful improvements to existing systems. You leave behind better documentation, tests, context, tools, and development patterns that make future work easier for both people and agents. Starting salary for this role is in the range of $130,000 - $165,000 and is dependent on numerous factors, including but not limited to location, work experience, and skills. This range does not include other compensation benefits. Axios' compensation philosophy takes into account the cost of labor differentials across the country. Because this is a remote-optional job posting, this salary range takes into account all possible locations within the United States, but candidates will only be eligible for the salary range for their location. Axios is committed to embracing artificial intelligence as a core part of how we work. All team members are expected to actively develop AI literacy and use AI tools to enhance their productivity, creativity, and efficiency. We invest in ongoing learning to ensure every employee is equipped to responsibly and effectively integrate AI into their daily workflows. What Axios brings to the table besides salary: 401(k) with employer match Robust PPO and High Deductible health insurance options on the Blue Cross Blue Shield network Employer Health Savings Account (HSA) contribution for the high deductible health plan option Dental and vision coverage Primary caregiver 12-week paid leave Birth-givers will have an additional 6-8 weeks depending on type of delivery, for a total of 18-20 weeks continuous leave Generous vacation policy, plus holidays One mental health day per quarter Annual learning and development stipend $100 monthly work-from-home stipend Tele-mental health services through Headspace OneMedical membership, including tele-health services Personal health advocacy resources through HealthAdvocate Inclusive fertility, hormonal health and family forming benefits through Carrot Fertility Access to the Axios “Family Fund”, which was created to allow employees to request financial support when facing financial hardship or emergencies Increased work flexibility for parents and caretakers Virtual company-sponsored social events A strong and positive work environment A commitment to an open, inclusive, and diverse work culture Equal Opportunity Employer Statement Axios is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, age, gender identity, gender expression, veteran status, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Axios makes hiring decisions based solely on qualifications, merit, and business needs at the time.

1 big thing: Axios is a growth-focused media company dedicated to helping people get smarter, faster on what matters. As we continue to scale, data plays a critical role in how we drive that mission forward. Why it matters: As an Analytics Engineer at Axios, you’ll serve as the primary interface for delivering insights to the business. You’ll design and maintain the curated layers of our data platform (Silver and Gold), and also own the dashboards and visualizations that translate those data products into actionable insights. By combining engineering rigor with business context and storytelling, you’ll ensure decision-making is faster, clearer, and aligned with Axios’ mission. In partnership with data engineers, data scientists, and product managers, you’ll transform raw and complex source data into well-structured data products, certified dashboards, and compelling visualizations that underpin reporting, experimentation, and advanced analytics. Responsibilities: Own the Silver and Gold layers of the medallion architecture: define, version, and maintain business metrics and semantic models. Build and maintain executive dashboards and visualizations that communicate key insights effectively. Define and enforce best practices for data visualization, storytelling, and stakeholder adoption. Build and maintain data marts and semantic layers that serve multiple domains across Axios. Review and certify dashboards for accuracy, consistency, and adherence to standards. Collaborate with data engineering to ensure Silver layer tables meet business needs. Implement data quality tests, documentation, and lineage tracking to ensure trust in analytics outputs. Serve as a bridge to data science, ensuring feature stores and model outputs are well-documented and reusable. Contribute to the hub-and-spoke model: rotate through responsibilities such as intake, quality assurance, and participation in the analytics hub, while serving as a strategic partner to stakeholders, helping them shape the right questions and identify the decisions their data should inform. Skills: 2-5+ years of experience in analytics engineering, BI development, or data visualization roles. Strong proficiency in SQL and experience with dbt or similar transformation frameworks. Expertise in BI and visualization tools (Looker, Tableau, Power BI, Mode, etc.). Familiarity with modern data stack (Snowflake, BigQuery, Redshift, or equivalent). Experience designing and modeling curated datasets, semantic layers or metric stores, and data marts that drive consistent and reliable decisions. Understanding of medallion architecture and data governance best practices. Solid grasp of versioning, testing, and CI/CD practices for data pipelines. Strong data storytelling and presentation skills; ability to communicate complex concepts clearly. Comfort working in a hub-and-spoke model, balancing central standards with domain-specific consulting. What success looks like: Business users rely on analytics engineers for both accurate data models and clear, actionable dashboards. Stakeholders see insights delivered through compelling visualizations that drive decisions. Data engineers know what to build in Silver because requirements are clearly defined upstream. Data scientists can discover and reuse well-documented features and model inputs. Leadership sees fewer instances of unreliable or inconsistent dashboards and more decisions influenced by consistent, well-visualized data. You help establish analytics engineering as the cornerstone of the data-to-decisions lifecycle at Axios. Starting salary for this role is in the range of $130,000 - $155,000 and is dependent on numerous factors, including but not limited to location, work experience, and skills. This range does not include other compensation benefits. Axios' compensation philosophy takes into account the cost of labor differentials across the country. Because this is a remote-optional job posting, this salary range takes into account all possible locations within the United States, but candidates will only be eligible for the salary range for their location. Axios is committed to embracing artificial intelligence as a core part of how we work. All team members are expected to actively develop AI literacy and use AI tools to enhance their productivity, creativity, and efficiency. We invest in ongoing learning to ensure every employee is equipped to responsibly and effectively integrate AI into their daily workflows. What Axios brings to the table besides salary: 401(k) with employer match Robust PPO and High Deductible health insurance options on the Blue Cross Blue Shield network Employer Health Savings Account (HSA) contribution for the high deductible health plan option Dental and vision coverage Primary caregiver 12-week paid leave Birth-givers will have an additional 6-8 weeks depending on type of delivery, for a total of 18-20 weeks continuous leave Generous vacation policy, plus holidays One mental health day per quarter Annual learning and development stipend $100 monthly work-from-home stipend Tele-mental health services through Headspace OneMedical membership, including tele-health services Personal health advocacy resources through HealthAdvocate Inclusive fertility, hormonal health and family forming benefits through Carrot Fertility Access to the Axios “Family Fund”, which was created to allow employees to request financial support when facing financial hardship or emergencies Increased work flexibility for parents and caretakers Virtual company-sponsored social events A strong and positive work environment A commitment to an open, inclusive, and diverse work culture Equal Opportunity Employer Statement Axios is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, age, gender identity, gender expression, veteran status, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Axios makes hiring decisions based solely on qualifications, merit, and business needs at the time.