Senior Software Engineer
New
E
EarnInFinancial Services
Mexico City, Mexico; Remote, MexicoFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years of professional software engineering experience, including 3+ years building infrastructure or internal tooling for developer teams
- Required Skills
- PythonGoCI/CDGitHub Actions
Requirements
- 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
- Hands-on experience building and deploying agentic or LLM-powered systems in production
- Practical familiarity with MCP patterns, tool-augmented workflows, or multi-step agent architectures
- Experience integrating with LLM APIs (Anthropic Claude, OpenAI, or equivalent)
- Understanding of tradeoffs around context management, latency, cost, and safety
- Experience with GitHub Actions or similar CI/CD platforms
- Daily use of AI-assisted development tools (Cursor, Claude Code, Copilot, or equivalent)
- Ability to define meaningful metrics for AI-assisted tooling and run time-bound experiments
Responsibilities
- 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.
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