Staff AI Engineer

San Francisco, United StatesRemotefull_timeVerifiedPosted 25 Jun 2026

About the role

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 B company, backed by over $100 million in funding from top-tier global investors, including QED, Castle Island, Switch Ventures, HTwenty, Monashees, and 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 shit 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 visionary and highly technical Staff AI Engineer to join our EngOps team within the new Enterprise AI squad. This role is central to our next phase of growth, focusing on designing, building, and scaling the core autonomous AI infrastructure that powers both our customer-facing product and internal engineering operations.

In this role, you will be the architect behind our "Maestro" (our central AI orchestrator) and its distributed execution systems. You will be instrumental in evolving our WhatsApp-based AI platform into a sophisticated, multi-agent enterprise system capable of reasoning, planning, and automating complex, multi-step tasks across critical internal and product functions (e.g., loans, payments, fraud).

You will act as a foundational technical anchor for EngOps, helping shape the future architecture of this new squad and analyzing what the division needs next as we scale. If you thrive at the intersection of deep software infrastructure, operational excellence, and agentic AI, this is your mission.

Responsibilities

Maestro & Orchestration Architecture: Architect, develop, and maintain the core infrastructure for our central AI orchestrator ("Maestro") and its connected execution agents to optimize engineering and enterprise operations.
Infrastructure-First AI Development: Lead the integration of AI agents into core product and operational infrastructure. Own the full lifecycle from containerization (Docker/Kubernetes) to CI/CD deployment, ensuring high availability, security, and post-launch stability.
LLMOps & Observability: Establish production-grade monitoring, tracing, and logging for complex agentic workflows within the EngOps ecosystem to track reasoning paths, tool-calling success rates, and latency bottlenecks.
Advanced Evaluation Pipelines: Design automated "evals-as-code" using LLM-as-a-judge, semantic similarity testing, and adversarial benchmarking to ensure agent safety, reliability, and groundedness.
Performance & Cost Engineering: Optimize RAG pipelines and agent loops for production constraints, implementing caching strategies, prompt compression, and model routing to balance inference costs with high performance.
Strategic Technical Leadership: Define operational best practices for AI deployment, asynchronous programming, and structured data validation. Help map out future team and infrastructure needs.

Requirements