. 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.
Qualifications
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.
Exceptional expertise in Python and deep knowledge of System Architecture. Mastery of core LLM APIs and agentic frameworks.
Proven experience implementing complex agentic systems, including RAG, tool-calling, vector databases, and advanced memory/state management.
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.
Requirements
8+ years of hands-on experience in software engineering.
Strong background in infrastructure and systems development.
At least 2 years dedicated to building and deploying production-grade AI applications focused on LLMs.
High ownership and comfort working in an early-stage squad environment.
Benefits
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
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.