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Senior Software Engineer

Earnin · Mexico City, Mexico

PresencialInglês

Sobre a vaga

Do anúncio da empresa · Earnin · publicado em 4 de setembro de 2026

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 those with the unique needs of 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 are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

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

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