ABOUT EARNIN

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for people living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and excited to bring on world-class talent to help shape the next chapter of our growth journey.

EarnIn is becoming an AI-native company, embedding AI agents into how we build, analyze, and operate across every function. Teams use AI Agents to move from ideas to execution faster. By letting agents handle repetitive tasks, our people can focus on judgment, creativity, and hard problems. We pair this experimentation with the strict review and security guardrails our regulated financial environment requires, always keeping a focus on privacy and the people who rely on our products.

As a company, we are becoming AI-native, and we encourage you to use AI tools throughout much of your interview process. If you use AI during the live interview, just say so; a quick, natural mention of how it helped and why you are using it is all we need. What we're evaluating is your judgment, reasoning, and ability to own and defend your work, not whether AI was involved. Some rounds, particularly those focused on your career history and past experiences, will not allow the use of AI, and we'll let you know of those in advance. When in doubt, ask your recruiter or interviewer directly.

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.