Lead AI Engineer (ML/LLM Ops & Agentic AI)

Location: Paris, France or remote in France; USA is also listed as an available location. Flexible remote and hybrid working options are available, with a final interview at the office.

Company

hirify.global develops secure, explainable AI agents and SaaS platform capabilities for the insurance industry.

What you will do

• Design and ship production-grade agentic workflows using LLM orchestration, tool calling, MCP, RAG, and structured outputs.
• Define reference architectures that determine which tasks are handled by models and which by deterministic code.
• Own LLMOps standards, including evaluation harnesses, prompt and agent versioning, OpenTelemetry tracing, cost and token governance, release gates, and tenant-aware data isolation.
• Own and evolve the Databricks-based ML platform, including Unity Catalog, MLflow, CI/CD to AKS serving, monitoring, and agent and prompt lifecycle capabilities.
• Design and deploy self-hosted open-weight foundation model infrastructure, own the inference layer and model optimizations, and collaborate with Cloud Ops on GPUs and clusters.
• Lead time-boxed AI proofs of concept, coach 2–5 engineers, conduct design and code reviews, and partner with product, data science, architecture, security, and SRE.

Requirements

• Proven experience building production agentic AI systems with Microsoft Agent Framework, OpenAI Agents SDK, PydanticAI, LangGraph, or custom frameworks, plus strong command of tool calling, MCP, RAG, and evaluation.
• High proficiency in Python, including strong OOP experience and the ability to design robust, maintainable software with clean code, appropriate design patterns, and software engineering best practices.
• Hands-on experience with experiment tracking, model registries, serving, and monitoring, ideally with Databricks and MLflow.
• Experience building backend services on Azure, Kubernetes, Terraform, and event-driven architectures.
• Solid machine learning foundations and the ability to critically assess new approaches.
• Experience leading technical initiatives across stakeholders and coaching or managing technical contributors, or clear motivation to do so.
• English fluency is required.

Nice to have

• Exposure to graph machine learning, fraud data, or insurance claims data.
• French language skills.

Culture & Benefits

• Flexible remote and hybrid working options.
• Competitive salary with a variable component tied to personal and company performance.
• Learning and development opportunities, including a monthly half-day Focus Friday.
• Generous paid time off and paid holidays.
• Mental health benefits and two paid volunteering days per year.

Hiring process

• Initial fit call with a Talent Acquisition Specialist.
• Two interviews assessing leadership and technical skills.
• Final round at the office with multiple interviews, including conversations with co-founders.