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Senior AI Platform Engineer – Agentic AI
PresencialTiempo completoAI EngineeringCybersecurity
Build reliable internal AI platforms, developer tooling, agentic workflows, and AI-powered infrastructure for engineering teams. The role combines hands-on software development, cloud infrastructure, DevOps, applied AI, observability, and security governance.
Responsabilidades
- Design and build internal AI platforms, SDKs, libraries, tools, and MCP servers
- Develop single-agent and multi-agent workflows with planning, delegation, state, memory, retries, fallbacks, and human approval
- Integrate AI capabilities into Kubernetes infrastructure and CI/CD pipelines
- Implement agent tracing, prompt and tool-call logging, latency and error monitoring, token and cost tracking, and failure analysis
- Apply security controls, guardrails, auditability, and governance to agent systems
- Own AI platform capabilities from architecture through production
- Identify AI opportunities with engineering and business teams and deliver scalable solutions
- Evaluate emerging AI frameworks, models, and cloud technologies
Requisitos
- At least 5 years of hands-on development experience with Python and/or TypeScript
- At least 2 years of hands-on production experience building LLM-powered applications, AI agents, multi-agent systems, or internal AI platforms
- Experience building asynchronous backend services and APIs with FastAPI or an equivalent modern framework
- Strong experience with Kubernetes, Helm, Docker, Jenkins, GitHub Actions, and AWS and/or Azure
- Hands-on experience with LangChain, LangGraph, Claude Agent SDK, and OpenAI and/or Anthropic APIs
- Experience with agent architecture, prompt and context engineering, tool or function calling, and structured outputs
- Experience building and integrating MCP servers and clients
- Experience implementing AI evaluations, regression tests, and production observability
- Understanding of AI guardrails, access controls, auditability, governance, and safe agent execution
Se valora
- Experience with Infrastructure as Code and GitOps
- Experience with Git-based collaborative workflows
- Experience evaluating emerging AI frameworks, models, and cloud technologies