AI Engineer, Freelance

Jobtailor; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Jobtailor is seeking a skilled Python Developer/ML Engineer to build production-grade GenAI agents and multimodal experiences. You will own agent lifecycles, implement AIOps/MLOps practices, and work across the full stack from orchestration layers to backend services, using ADK, Langchain, LangGraph, and Kubernetes.

The role emphasizes strong Python expertise, production deployments, and collaboration with cross-functional teams to enable scalable GenAI features in a fast-paced environment.

Qualifications

• Master's degree in Computer Science, Data Science, or a similar technical field.
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Responsabilités

• Own the production lifecycle of AI agents and agentic platforms, ensuring robust monitoring, versioning, evaluation pipelines, and reliability.
• Design, develop, and deploy production-ready agent workflows and orchestration layers using Python frameworks (ADK, Langchain, LangGraph).
• Collaborate with R&D teams to build MCP servers and backend services that agents interact with, and contribute to GenAI Center of Expertise.

Connaissances

Python

LLM deployment

CI/CD

Git

Observability

AIOps/MLOps

Formation

Master's degree in Computer Science

Outils

ADK

Langchain

LangGraph

n8n

Kubernetes

Vertex AI

Description du poste

Overview

Build production agents — design, develop, and deploy goal-oriented AI agents and multimodal/conversational experiences using frameworks like Google ADK, Langchain, LangGraph, combined with orchestration tools like n8n where appropriate. Own the production lifecycle of what you ship — establish robust AIOps/AgentOps practices (monitoring, versioning of agent blueprints, evaluation pipelines, reliability) within your team's scope. Contribute to the shared Agentic Platform (Core pillar) — gateways, evaluation frameworks, observability, MaaS/AaaS APIs — so feature teams build faster on solid foundations. Build agent-side integrations (Feature pillar) — develop the MCP servers and backend services that agents need to interact with enterprise systems, in partnership with other R&D teams (and picking up the work yourself when a partner team doesn't have bandwidth). Be the Python referent in your team — own production-quality Python, enforce strong SWE principles (unit tests, CI/CD, Git, code review), and bring AIOps/MLOps best practices wherever you sit. Build a working expertise on agentic design patterns (eval, guardrails, multi-agent orchestration) and share it with AI champions and AI builders across the company as the GenAI Center of Expertise takes shape. Engage with stakeholders — talk to internal teams to understand operational pain points and translate them into measurable GenAI solutions. You don\'t lead cross-team architecture, but you should be credible across the org.

Requirements

• Master\'s degree in Computer Science, Data Science, or a similar technical field.
• 3+ years as a Python Developer or ML Engineer, with a recent focus on deploying LLM-powered solutions in production.
• Mastery of Python for enterprise-level development, strong knowledge of core software engineering principles, and hands-on experience with AIOps/MLOps (unit tests, CI/CD, Git, observability). You should be comfortable being your team\'s reference on these topics.
• Proven experience building production-ready agent workflows, orchestration layers, or platforms using Python frameworks (ADK, Langchain, LangGraph).
• Practical experience with modern cloud platforms (Vertex AI, Kubernetes or equivalents) for deploying scalable GenAI services.
• Strong versatility and a demonstrated willingness to work across the full stack and across functional expertises.
• Entrepreneurial mindset, high autonomy, and the ability to turn ambiguous, high-level business goals into concrete, efficient GenAI features.
• Fluent technical English (written and verbal) — mandatory.