POSITION SUMMARY

Join our DevelSoper Experience team to design and ship AI-native tooling and agentic workflows that meaningfully accelerate the way EarnIn engineers build, ship, and operate software, and help set a new bar for what engineering productivity looks like. This is a remote position, though it could also be a hybrid role from our Mexico City office as part of our expanding site. EarnIn offers excellent benefits for our employees, including healthcare, internet and cell phone reimbursement, a learning and development stipend, and potential opportunities to travel to our Mountain View headquarters. Our salary ranges are determined by role, level, and location. We are unable to provide visa sponsorship or immigration support for this position.

WHAT YOU'LL DO

• Draw on firsthand experience with the friction, toil, and frustrations that slow engineering teams down and use that empathy to build tools and automation that actually solve the right problems.
• Drive the design, development, and implementation of tools, systems, and processes that accelerate engineering velocity, reduce manual effort, and raise the quality bar for software delivery.
• Use the latest AI capabilities LLM APIs, agentic workflows, MCP patterns, and AI-assisted development environments to fundamentally rethink what a high-productivity engineering team looks like.
• Architect and operate multi-step agentic systems with well-defined inputs, outputs, validation checkpoints, and human-in-the-loop guardrails that run reliably at scale.
• Embed AI-assisted capabilities into CI/CD pipelines and GitHub Actions workflows to improve build reliability, code quality feedback loops, and developer toil reduction.
• Guide and advise product engineering teams on best practices for building observable, scalable systems acting as a force multiplier across the org, not just within DevX.
• Partner directly with engineering teams to identify high-friction workflows, translate them into structured AI-assisted automation, and measure impact against defined success metrics.
• Instrument AI-powered features with end-to-end logging, monitoring, evaluation, and their lifecycle from pilot through iteration or retirement.
• Document patterns, usage guidance, and best practices so proven workflows can be consistently adopted and extended across the org.

WHAT WE'RE LOOKING FOR

• 4+ years of professional software engineering experience, including 3+ years building infrastructure or internal tooling for developer teams; fluency in Python or Go.
• Firsthand experience with the tools, workflows, and pain points of software engineering teams; you've felt the friction yourself and know how to fix it.
• Hands-on experience building and deploying agentic or LLM-powered systems in production, including practical familiarity with MCP patterns, tool-augmented workflows, or multi-step agent architectures.
• Some experience integrating with LLM APIs (Anthropic Claude, OpenAI, or equivalent) and an understanding of tradeoffs around context management, latency, cost, and safety.
• Experience with GitHub Actions or similar CI/CD platforms, including building custom workflows, reusable actions, or automation that operates on code or pull requests.
• Daily use of AI-assisted development tools (Cursor, Claude Code, Copilot, or equivalent); treat these as core to how you work, not a nice-to-have.
• Ability to define meaningful metrics for AI-assisted tooling and run time-bound experiments to validate impact.
• Clear written and verbal communication skills, comfortable advising and influencing partner engineering teams in a distributed environment.
• Experience using AI-assisted development tools (e.g., Copilot, Cursor, LLMs)

#LI-Remote #LI-Hybrid