- 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.
- Experience: 8+ years of hands-on experience in software engineering, with a strong, proven background in infrastructure and systems development, and at least 2 years dedicated to building and deploying production-grade AI applications focused on LLMs.
- Technical Mastery: Exceptional expertise in Python and deep knowledge of System Architecture. Mastery of core LLM APIs and agentic frameworks.
- Agentic System Expertise: Proven experience implementing complex agentic systems, including RAG, tool-calling, vector databases, and advanced memory/state management.
- Execution & Autonomy: High ownership and comfort working in an early-stage squad environment—someone who can independently analyze operational bottlenecks, propose architectural solutions, and code them.
- Nice to have: Hands-on experience or active experimentation with Open CLAW, Hermes, or advanced open-source AI Agent frameworks.
- These are the applicable requisites, although equivalent competencies in any of the above will also be considered.
- Competitive salary
- Initial stock options grant
- Annual performance bonus
- Health, dental, and vision plans
- 401(k) with employer match
- Continuous learning opportunities
- Unlimited PTO
- Paid parental leave
- Empowering opportunities for growth in a dynamic entrepreneurial environment
- Competitive salary
- Initial stock options grant
- Annual performance bonus
- Health, dental, and vision plans
- Remote work environment, although we have offices in Miami and México City and would love to work in hybrid model if you are up to it.
- Continuous learning opportunities
- Unlimited PTO
- Paid parental leave
- Empowering opportunities for growth in a dynamic entrepreneurial environment
Skills Required
- 8+ years hands-on software engineering with strong infrastructure and systems development experience
- At least 2 years building and deploying production-grade AI applications focused on LLMs
- Exceptional expertise in Python
- Deep knowledge of system architecture
- Mastery of core LLM APIs and agentic frameworks
- Proven experience implementing agentic systems including RAG, tool-calling, vector databases, and advanced memory/state management
- Experience with containerization (Docker) and orchestration (Kubernetes) through CI/CD for production deployments
- Experience establishing production-grade observability: monitoring, tracing, and logging for agentic workflows
- Designing automated evaluation pipelines (evals-as-code), semantic similarity testing, and adversarial benchmarking
- Performance and cost optimization of RAG pipelines and agent loops (caching, prompt compression, model routing)
- High ownership and ability to operate autonomously in an early-stage squad environment
- Hands-on experience or experimentation with Open CLAW, Hermes, or advanced open-source AI Agent frameworks
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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