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Lead AI Engineer
Job in
Tarrytown, Westchester County, New York, 10591, USA
Listed on 2026-08-26
Listing for:
Regeneron
Full Time
position Listed on 2026-08-26
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Software Architect, Machine Learning/ ML Engineer, Cloud Engineer - Software
Job Description & How to Apply Below
Lead AI Engineer
Regeneron is seeking an experienced Lead AI Engineer to serve as a technical leader within the AI Strategy & Execution organization. In this role, you will architect and deliver enterprise-scale AI capabilities — spanning intelligent agents, LLM-powered applications, and AI platform services — that accelerate drug discovery, clinical research, and enterprise productivity. You will lead a team of engineers, drive cross-functional collaboration, and communicate AI strategy to senior stakeholders, all while maintaining a strong hands-on presence in Python development and AI systems design.
AIEngineering & Intelligent Systems
- Lead end-to-end design, development, and deployment of enterprise AI applications and LLM-powered systems, ensuring production-grade quality, security, and scalability.
- Design and build AI Agents and autonomous systems using agentic frameworks including Lang Chain, Lang Graph, Strands, and CrewAI, applying ReAct, tool-use, planning, and memory management patterns.
- Develop and operate MCP (Model Context Protocol) servers for standardized, secure integration between AI agents and enterprise data sources.
- Apply advanced LLM techniques — prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) — to build intelligent, context-aware applications.
- Architect RESTful APIs that expose AI capabilities to internal platforms and downstream business applications.
- Administer and continuously evolve the enterprise LLM and AI Gateway platform, including model routing, access controls, rate limiting, usage observability, and multi-model orchestration.
- Evaluate and onboard new foundation models (OpenAI, Anthropic, AWS Bedrock, and others) in alignment with enterprise security and compliance standards.
- Lead, mentor, and manage a team of AI engineers, conducting code reviews, setting technical standards, and fostering a culture of engineering excellence.
- Contribute to the organization's AI roadmap through architectural design reviews, technical strategy, and proof-of-concept development.
- Troubleshoot complex issues across AI model serving, APIs, and platform layers.
- Partner with business units, data scientists, and clinical research teams to identify AI opportunities and translate them into scalable technical solutions.
- Serve as the primary technical point of contact for enterprise AI platform discussions, presenting findings and recommendations to senior leadership.
- Engage with external vendors, cloud providers, and AI research organizations to evaluate and integrate emerging capabilities.
- 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, with at least 3 years in a technical lead or senior individual contributor role.
- Expert-level Python development skills, including production REST API development with FastAPI.
- Proven hands-on experience building AI Agents, MCP Servers, and LLM-powered applications using frameworks such as Lang Chain, Lang Graph, Strands, or CrewAI.
- Hands-on experience with vector databases (Milvus DB preferred) for RAG and semantic search pipelines.
- Experience administering LLM API gateway platforms, including model routing, observability, access governance, and multi-model orchestration.
- Experience with foundation models from OpenAI, Anthropic, AWS Bedrock, and other major providers.
- Working knowledge of AWS cloud services relevant to AI workloads (Sage Maker, Bedrock, EKS, Lambda, S3);
Kubernetes and CI/CD experience is a plus. - Experience in the biotechnology, pharmaceutical, or healthcare industry preferred.
- Programming:
Python (expert-level). - AI Frameworks & Runtimes:
Lang Chain, Lang Graph, Strands, CrewAI; AWS Bedrock Agent Core. - LLM Techniques:
Prompt engineering, fine-tuning, RAG, vector databases (Milvus DB preferred). - AI Platform: LLM Gateway management, model routing, multi-model orchestration, Tensor Flow, PyTorch.
- API…
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