AI Engineer (Agents)

AI in this role

openailangchainlanggraphcrewaiweights-and-biases

ragai-agents

About Us
At Félix, we're building the financial ecosystem for Latin immigrants in the U.S., starting with a revolution in remittances. Our core product is an AI-powered chatbot built on WhatsApp, allowing our users to send money home as easily as sending a text message. We leverage cutting-edge technology like AI, blockchain, and stablecoins to make cross-border payments faster, more affordable, and more accessible than ever before.
We are a hyper-growth Series C company, backed by over $200 million in funding from top-tier global investors, including QED, Castle Island, Switch Ventures, HTwenty, Monashees, and Andreessen Horowitz with support from General Catalyst Customer Value Fund. This isn't just about the numbers; it's a testament to the trust our investors have in our vision and our team. Additionally, Félix was selected as an “Endeavour Entrepreneur” and was a recipient of the CrossTech Fintech Startups Award. We are a group of extremely talented and dedicated high-performers, united by our shared obsession with a single goal: empowering our customers. We are all owners of Félix, driven by a bias for action and a true experimentation spirit to get things done with urgency and focus.
Joining Félix means you will be part of a team building a legacy, a company that will outlive us all. This is a rare opportunity to apply your skills to a deeply meaningful mission—serving a community that has been underserved for too long. We are a team that is fiercely loyal to each other, where radical transparency and constructive feedback are how we grow and push for excellence. We are bold, we care less about what others are doing, and more about creating sustainable value and a product that truly makes our users' lives better. We are building the future, today.
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. We are building a world-class AI team and believe great talent comes in various shapes. We are open to hiring at the Semi-Senior, Senior, or Staff level. We will calibrate your role, title, and compensation package based on your technical depth, architectural ownership, and the scope of impact you’ve historically delivered.
You will be instrumental in evolving our WhatsApp-based AI platform beyond simple Q&A into a sophisticated, multi-agent system capable of reasoning, planning, and executing complex, multi-step tasks across our critical functions (e.g., loans, payments, fraud). You will partner closely with different engineering teams and PMs to translate our AI strategy into a tangible roadmap and bring it to life. 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. You won't just build "demos"; you will ship hardened systems 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.
These are the applicable requisites, although equivalent competencies in any of the above will also be considered.

What We OfferBase Salary (by level) Flexible depending on location and interview performance

- Mid: $105,000–$170,000
- Senior: $160,000–$245,000
- Staff: $230,00–$320,000
Initial stock options grant
Annual performance bonus
Health, dental, and vision plans
Continuous learning opportunities
Unlimited PTO
Paid parental leave
Empowering opportunities for growth in a dynamic entrepreneurial environment

Equal Opportunity Employer
At Félix, we are committed to providing equal employment opportunities to all qualified employees and applicants without regard to race, religion, nationality, sex, sexual orientation, gender identity, age, or disability. This policy applies to all terms and conditions of employment, including recruitment, hiring, placement, promotion, training, compensation, benefits, and termination.
Want to learn more about our privacy practices? Check out our Privacy Policy.

How we score this

AI Engineer (Agents) at Felix scores 98 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagAI AgentsOpenAILangChainLangGraphCrewAIWeights And Biases

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
What are the limits of OpenAI that you've run into, and how did you work around them?
What's a project where you used LangChain hands-on?
Walk me through how you've used LangGraph in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Rag, AI Agents, OpenAI, LangChain, and LangGraph. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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