AI Engineer (Enterprise)

Felix is hiring an AI Engineer (Enterprise) in San Francisco, United States. It pays $105k-$170k a year and Level rates it ; you can apply on Level.

AI in this role

openailangchainlanggraphcrewaiweights-and-biases

ragai-agents

About Us
At Félix, we are building the indispensable financial companion for Latinos in the US. We combine an AI-powered, conversational-first interface with real-time financial infrastructure to make cross-border money movement as easy as sending a text. Starting with fast, affordable remittances powered by AI and crypto rails, we are expanding into credit, savings, and wallet services to support the complete immigrant financial journey. Our ambition is to deliver a white-glove financial experience with the simplicity of a conversation to a community the traditional financial system has historically overlooked.
We are a hyper-growth Series C company, backed by over $300 million in funding from top-tier global investors, including Andreessen Horowitz, QED, Castle Island, Switch Ventures, HTwenty, Monashees, 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 “Endeavor Entrepreneur” and was a recipient of the CrossTech Fintech Startups Award.
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 because we are obsessed with our customers. We get things done with urgency and focus, driven by extreme ownership over our impact. We collaborate without ego, fostering radical transparency and fierce loyalty so we can grow together. Because we aim for insanely great rather than just good enough, we stay insatiably curious—always experimenting, building the future today, and delivering a product that truly makes our users' lives better.
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 rate this

AI Engineer (Enterprise) at Felix rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

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

Key facts

AI Engineer (Enterprise) is an open job at Felix.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $105k-$170k a year.
The role is based in San Francisco, United States.
The job was posted on September 22, 2026.
Seniority: senior.
Applications are handled by Felix. Apply on Felix

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsOpenAILangChainLangGraphCrewAIWeights And Biases

Also common in AI engineer jobs at this level

Machine learning AWS Azure Google Cloud PyTorch Java

Pay

This job starts at: $105k
Typical AI engineer job: $181k

This posting starts 42% below the typical AI engineer job. See AI engineer jobs

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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