- Translate AI priorities into technical plans with scope, requirements, milestones, success metrics, acceptance criteria, and named owners.
- Turn incomplete briefs into testable hypotheses, baselines, and measurable outcomes.
- Coordinate technical dependencies across Engineering, Product, Data, FDE, AI Enterprise, and platform teams.
- Drive technical decisions with engineers: challenge assumptions, make trade-offs explicit, and record the outcome.
- Manage execution and risk: track commitments, remove blockers, and escalate early with a recommendation.
- Coordinate evaluations and deployment readiness, including quality, latency, cost, and permissions risks, and verify that FDE integrations work in the receiving team’s environment.
- Secure named owners for support, monitoring, and maintenance, and measure whether each solution solved the intended problem.
- Work with AISec and the AI Governance Committee so reviews happen early.
- Turn project lessons into reusable briefs, checklists, decision records, and handoff standards.
- Technical program leadership. Proven experience leading complex technical programs or software delivery across several teams, with specific examples of your own judgment, design contributions, decisions, and results.
- Hands-on technical fluency. Practical skills in Python, SQL, APIs, authentication, Git, and testing. Comfortable using at least one LLM SDK, such as OpenAI or Google, to prototype integrations and debug issues. You understand data modeling, pipelines, and enterprise integration patterns.
- Agent and evaluation knowledge. Experience with tool calling, multi-step orchestration, state, structured outputs, human review, and fallbacks. You can assess quality, latency, cost, and permissions risks, and define useful evaluations.
- Operational rigor. You establish baselines, validate assumptions through experiments, and balance sophistication with operational constraints.
- Communication and ownership. A track record of translating between business and engineering teams, influencing without formal authority, mentoring others, and escalating decisions early. Bring examples of solution designs, evaluation decisions, or delivery outcomes; confidential work can be discussed without sharing proprietary material.
- Applied LLM work used by real users
- RAG and vector database experience
- Experience deploying into environments owned by other teams
- Experience in a regulated or data-sensitive setting such as fintech
- Experience with CX, support, or compliance metrics such as AHT, FCR, CSAT, and SLA
What We Offer
- Competitive salary
- Initial stock options grant
- Annual performance bonus
- Unlimited PTO
- Paid parental leave
- Hybrid work setup
- Health, dental, and vision plans
- Continuous learning opportunities
- Empowering opportunities for growth in a dynamic entrepreneurial environment
Equal Opportunity Employer
Skills Required
- Proven experience leading complex technical programs or software delivery across multiple teams, including demonstrated judgment, design contributions, decisions, and results.
- Practical proficiency with Python, SQL, APIs, authentication, Git, and software testing.
- Experience using at least one LLM SDK, such as OpenAI or Google, to prototype integrations and debug issues.
- Understanding of data modeling, data pipelines, and enterprise integration patterns.
- Experience with tool calling, multi-step orchestration, state management, structured outputs, human review, and fallback mechanisms.
- Ability to evaluate AI quality, latency, cost, and permissions risks and define useful evaluations.
- Experience establishing baselines, validating assumptions through experiments, and balancing sophistication with operational constraints.
- Track record of translating between business and engineering teams, influencing without formal authority, mentoring others, and escalating decisions early.
- Applied LLM work used by real users.
- Experience with retrieval-augmented generation and vector databases.
- Experience deploying solutions into environments owned by other teams.
- Experience in a regulated or data-sensitive setting such as fintech.
- Experience with customer experience, support, or compliance metrics such as AHT, FCR, CSAT, and SLA.
What We Do
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, the Félix founders were selected as “Endeavour Entrepreneurs” and were recipients 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.





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