Lead Python Engineer, AI Agents

Lead Python Engineer, AI Agents (GCP)

Freelance mission in Boulogne-Billancourt (Île-de-France, hybrid). You will join a global technology organization to strengthen an AI agent platform already running in production on Google Cloud, for an end client in the industrial sector.

The challenge

The platform is live and the agents are serving real users. What it needs now is not research, it is production engineering: agents that stay reliable at scale, whose cost, security, quality and supervision are under control. You own that layer and you lead the developers who build it.

Responsibilities

• Set up, maintain and evolve the AI agents: functional coverage, specialization, inter-agent collaboration and use of standards.
• Manage security and ACLs, and integrate monitoring and reporting on agent activity.
• Optimize performance and running costs of the agents.
• Integrate quality evaluation mechanisms and guarantee scale-up.
• Work with DevOps to keep the platform stable and scalable, and guarantee the SLA.
• Lead a team of developers, challenge the product vision and drive design, development and operations.
• Collaborate with Solution Architects and enforce good practices in an agile setup.

Requirements

• 7+ years on similar missions, with proven technical leadership.
• Expert level Python back-end development.
• Strong command of LangGraph or ADK.
• Hands-on experience putting LLM agents into real production, including cost, security, quality and supervision.
• Solid knowledge of Generative AI, RAG, corpus, LLM, agents and prompts.
• Good knowledge of Google Cloud Platform.
• LangSmith or an equivalent observability tool.
• Experience leading and growing a team of developers.
• Technical English, spoken and written.

Nice to have

• Java and Spring frameworks, OpenID Connect and OAuth 2.
• Agent-oriented testing tooling, RESTful API design, application design patterns.
• SQL and PostgreSQL, MongoDB, vector databases.
• Git, TDD, pair and mob programming, code review.
• Streaming architectures and data processing systems.
• DevOps, managed service platforms, GDPR and AI ethics.
• Code assistants such as GitHub Copilot, agile methodologies, SAFe certification.