
Real job — pulled straight from Félix’s careers page · Verified November 7, 2026 · No reposts.
Job description
Félix is hiring a Senior AI Engineer — a full-time, based in Mexico City role. Apply directly on Félix's careers page below.
Senior AI Engineer, Ops Labs
Location: Mexico City
Department: Engineering
Location Type: HYBRID
Employment Type: FULL_TIME
About Us
About the Role
What You’ll Own
- Ops-Integrated AI Solutions: Partner with Ops leadership to transform operational friction into AI-assisted workflows. Design end-to-end solutions that span: predictive triggers, LLM-powered categorization, decision automation, and alert systems.
- Production-Grade Agent Architecture: Architect, ship, and maintain stateful AI agents that take real actions in ops workflows: calling tools, moving cases between queues, and carrying state across a case’s full lifecycle. You’ll use Python and modern frameworks (Google ADK, LangGraph, CrewAI, etc.), and the bar is shipped AI agents that handle real 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 ops systems (CX platform, compliance and hold queues, transaction tooling) with least-privilege access. 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. This includes trajectory evals that check whether an AI agent called the right tools in the right order, plus business metrics like resolution time, escalation rate, and CX agent override rate.
- 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.).
- Human-in-the-Loop & Autonomy Design: Define what each AI agent does on its own, what it only recommends, and what it never touches. Build confidence thresholds, escalation to CX agents, approval gates for irreversible actions, and audit trails for every decision.
Requirements
- Experience: 5+ 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 at least one core LLM API or framework (OpenAI SDK, Google AI SDK, CrewAI, LangChain, etc.).
- Agentic System Knowledge: Proven experience shipping AI agents to production that take actions, not just answer questions. This includes tool calling, multi-step orchestration, state management, human-in-the-loop escalation, guardrails, and failure handling (fallbacks, rollback). RAG and vector databases are a plus.
- 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.
- Operational Rigor: Demonstrated ability to translate ambiguous operational briefs into testable hypotheses. Comfortable with incomplete specs, can ask clarifying questions about success metrics, and understand trade-offs between technical sophistication and operational constraints. Experience validating assumptions via experiments.
- Execution & Communication: Proven ability to translate high-level business needs into concrete, maintainable, and well-tested code.
- Ops Experience: Experience building AI for CX, support, compliance, or other operations teams. Familiarity with ops metrics like AHT, FCR, CSAT, and SLA is a strong plus.
- These are the applicable requisites, although equivalent competencies in any of the above will also be considered.
What We Offer
- Competitive salary
- Initial stock options grant
- Annual performance bonus
- Unlimited PTO
- Paid parental leave
- Work model: currently fully remote, with a future transition to a hybrid setup
- Health, dental, and vision plans
- Continuous learning opportunities
- Empowering opportunities for growth in a dynamic entrepreneurial environment
Equal Opportunity Employer
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Frequently asked questions
What skills are required for Senior AI Engineer at Félix?
The required skills for Senior AI Engineer at Félix include: Python, AI, Machine Learning, Generative AI, LangChain, Docker, Kubernetes, CI/CD, Git, GitHub, RAG.
What is the seniority level for Senior AI Engineer at Félix?
Senior AI Engineer at Félix is a Senior level position.
How do I apply for Senior AI Engineer at Félix?
You can view the full description and apply for Senior AI Engineer at Félix on EchoJobs: https://echojobs.io/job/f-lix-senior-ai-engineer-ops-labs-zlnnt.