Software Engineer

Axios is a growth-focused media company that delivers news to readers. The Full Stack Software Engineer builds and scales audience-facing products, publishing tools, and the interfaces, services, APIs, and data flows behind them, using AI-native development practices.

Responsibilities:

• 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
• Create accessible, responsive, and maintainable interfaces using JavaScript or TypeScript, React, and modern web frameworks such as Next.js
• 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
• 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
• Write automated tests, improve performance, and contribute to logging, metrics, tracing, security, and operational reliability
• 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
• 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

Requirements:

• 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
• 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
• 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
• 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
• Experience building production interfaces with JavaScript or TypeScript and React
• 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
• Experience with relational databases, SQL, schema design, transactions, and migrations
• Experience with unit and integration testing, accessibility, input validation, authentication, authorization, and common web security practices
• 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
• Ability to explain technical decisions, risks, blockers, and tradeoffs clearly to engineering and cross-functional partners
• Curiosity about rapidly changing models, tools, and development practices, paired with an evidence-based approach to evaluating them
• 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
• Experience building production interfaces with JavaScript or TypeScript and React, preferably with Next.js or a comparable modern framework