Lead AI Engineer: Agentic AI & LLM Ops

Shift Technology; Paris; Híbrido; EUR 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible remote options

Hybrid work model

Competitive salary with performance</n

Learning & Development

Generous PTO

Mental health benefits

Volunteer days

Descripción de la vacante

Shift Technology is seeking an experienced Lead AI Engineer to drive LLMOps and build agentic AI systems in production. You will lead a small team while staying hands-on, collaborating with data science, software engineering, and product leadership to prototype and ship high-impact AI capabilities.

You will own the Databricks-based ML platform, implement OpenAI/Agent frameworks, and guide the architecture for self-hosted models, tool calling, and reliable governance.

Formación

• Proven experience building production-grade agentic AI systems.
• Hands-on MLOps with experiment tracking, model registry and serving.
• Strong Python and software engineering practices.

Responsabilidades

• Design and ship production-grade agentic workflows (LLM orchestration, tool calling, MCP, RAG).
• Own LLMOps standards: tracing, versioning, governance and release gates.
• Be technical owner of Databricks-based ML platform and CI/CD to serving on AKS.
• Design and optimize self-hosted open-weight models with Cloud Ops collaboration.
• Lead POCs on emerging AI techniques and translate to production.
• Coach and grow a team of 2–5 engineers and collaborate with stakeholders.

Conocimientos

Agentic AI

MLOps

Python

Leadership

English fluency

Herramientas

Databricks

MLflow

Azure

Kubernetes

Terraform

Descripción del empleo

Shift Technology is seeking an experienced Lead AI Engineer to drive LLMOps and build agentic AI systems in production. You will lead a small team while staying hands-on, collaborating with data science, software engineering, and product leadership to prototype and ship high-impact AI capabilities.

You will own the Databricks-based ML platform, implement OpenAI/Agent frameworks, and guide the architecture for self-hosted models, tool calling, and reliable governance.