Lead AI Engineer

Regeneron seeks a Lead AI Engineer in its Digital Transformation – AI Strategy & Execution department to lead enterprise AI capabilities for drug discovery, clinical research and productivity. The role combines hands-on Python engineering and AI systems design with team leadership and communication of technical strategy.

Responsibilities

• Design, develop and deploy secure, scalable, production-grade AI applications, LLM-powered systems and intelligent agents. Use agentic frameworks and ReAct, tool-use, planning and memory patterns; develop Model Context Protocol servers to connect agents securely with enterprise data.
• Apply prompt engineering, fine-tuning and retrieval-augmented generation. Architect vector databases for semantic search and knowledge retrieval, and build RESTful APIs exposing AI capabilities.
• Manage the enterprise LLM and AI Gateway platform, including model routing, access controls, rate limiting, observability and multi-model orchestration. Evaluate foundation models against security and compliance standards, and troubleshoot model-serving, API and platform issues.
• Lead and mentor AI engineers, review code, set technical standards and contribute to architecture reviews, proofs of concept and the AI roadmap. Work with business units, data scientists and clinical research teams; present recommendations to senior leaders and engage external technology partners.

Qualifications

• Bachelor’s, Master’s or Ph.D. in Computer Science, Computer Engineering, Artificial Intelligence or a related technical field; 7–10 years of progressive software and AI engineering experience, including at least 3 years as a technical lead or senior individual contributor.
• Expert Python and production FastAPI experience; hands-on work with AI agents, MCP servers, LLM applications, vector databases and LLM gateway administration. Familiarity with major foundation-model providers and AWS AI services is required. The posting lists TensorFlow, PyTorch, Docker, Terraform, Databricks, Dataiku, Postgres, Redis, NoSQL databases and AI-workload monitoring among its technical competencies.
• AWS Certified Machine Learning – Specialty certification is required. Biotechnology, pharmaceutical or healthcare experience, Milvus DB, Kubernetes and CI/CD experience are preferred or noted as pluses. AWS Certified Solutions Architect – Professional and Certified Kubernetes Administrator certifications are nice to have. Strong communication, cross-functional delivery and problem-solving skills are expected.

This is a full-time role with a stated annual salary range of $109,900.00–$179,300.00. On-site expectations for this particular role should be confirmed with the recruiter or hiring manager.