Lead AI Engineer

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Lead AI Engineer

Hybrid in United States of America: New York, United States of America: Chicago

AI Solution Engineering& 13 others

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Join a global engineering team reimagining insurance technology through intelligent automation. You will design and deploy production-grade Agentic AI systems powered by LLMs, RAG, and document intelligence, transforming how brokers and underwriters operate and enabling smarter, faster business decisions at scale.

EPAM is where tech talent thrives-building groundbreaking solutions, advancing your skills through world-class learning platforms, and working alongside a global community of problem-solvers to make the future real.

Req.#1090479031

Responsibilities

• Design, develop, and deploy production-grade Agentic AI solutions that automate complex insurance workflows, reducing turnaround times and increasing operational productivity

• Build AI-powered applications leveraging LLMs, RAG, document processing, information extraction, classification, and agent-based architectures at enterprise scale

• Own the end-to-end AI product lifecycle, from ideation and rapid prototyping through to deployment, monitoring, and continuous performance improvement

• Develop robust AI evaluation frameworks encompassing testing, monitoring, performance measurement, and hallucination detection to ensure production-level reliability

• Collaborate directly with brokers, underwriters, and operations teams to identify high-impact AI adoption opportunities and translate business challenges into scalable solutions

• Mentor engineers, champion modern AI development best practices, and research emerging technologies to continuously advance the intelligence of the platform

Requirements

• 5 to 8+ years of experience in Software Engineering, AI/ML, or related domains, with a Bachelors or Masters degree in Computer Science, Engineering, or equivalent practical experience

• Strong proficiency in Python with proven experience building and delivering AI-powered products end to end, from concept through to production deployment

• Hands-on experience with Large Language Models, Retrieval-Augmented Generation, information extraction, document understanding, classification models, and agentic AI workflow design

• Solid foundation in cloud platforms, containerization using Docker, CI/CD pipelines, monitoring, observability, and secure data handling within production-grade environments

• Experience with API design, system design, full-stack application development, and working knowledge of TypeScript/Angular or .NET/C# as a complementary skill

• Strong analytical, problem-solving, and communication skills, with the ability to clearly articulate complex AI concepts and trade-offs to non-technical business stakeholders