AI Engineer (Agents)

About the role

We are seeking a proactive and highly skilled AI Engineer to join our core AI team. This role is central to Félix's next phase of growth, focusing on designing, building, and scaling autonomous AI Agents that will integrate directly into our product and internal operations.

This is a unique opportunity to apply a bias toward action and an experimentation spirit to solve deeply meaningful, real-world problems for Latin immigrants in the U.S. If you thrive in a rapid-iteration environment and want to build the infrastructure that powers a hyper-growth fintech, this is your mission.

Responsibilities

• Production-Grade Agent Architecture: Architect, develop, and maintain scalable, stateful AI agents using Python and modern frameworks (Google ADK, LangGraph, CrewAI, etc.) that handle real-world edge cases.
• LLMOps & Observability: Establish production monitoring for agentic workflows. Implement tracing and observability (e.g., LangSmith, Arize Phoenix, or Weights & Biases) to track reasoning paths, tool-calling success rates, and latency bottlenecks.
• End-to-End Production Integration: Lead the integration of AI agents into core product infrastructure (Payments, Fraud, etc.). Own the full lifecycle, from containerization (Docker/Kubernetes) to CI/CD deployment and post-launch stability.
• Advanced Evaluation Pipelines: Move beyond basic metrics. Design automated "evals-as-code" using LLM-as-a-judge, semantic similarity testing, and adversarial benchmarking to ensure agent safety and groundedness before every release.
• Performance & Cost Engineering: Optimize RAG pipelines and agent loops for production constraints. Implement caching strategies, prompt compression, and model routing to balance inference costs with high-performance requirements.
• Technical Leadership: Mentor junior engineers on software craft. Drive best practices in asynchronous programming, error handling for non-deterministic outputs, and structured data validation (Pydantic, etc.).

Requirements

• Experience: 7+ years of hands-on experience in software engineering, with at least 2 years dedicated to building and deploying production-grade AI/ML applications, specifically focused on Large Language Models (LLMs) or generative AI.
• Technical Mastery: Mandatory expertise in Python and deep familiarity with 1 core LLM APIs and frameworks (OpenAI SDK, Google AI SDK, CrewAI, LangChain, etc.).
• Agentic System Knowledge: Proven experience implementing agentic systems, including knowledge of RAG, vector databases, and memory/state management.
• Engineering Fundamentals: Strong understanding of software development best practices, version control (Git/GitHub), and CI/CD pipelines. Experience with personal projects or demonstrable contributions on GitHub is a strong plus.
• Execution & Communication: Proven ability to translate high-level business needs into concrete, maintainable, and well-tested code.