Lead AI Engineer at MassMutual

MassMutual's Data Science team is seeking an impact-driven Lead AI Engineer to join our high-performing, cross-functional team. In this role, you will lead the design and deployment of advanced AI solutions that drive strategic decision-making and business transformation. You'll apply cutting-edge techniques in machine learning, generative AI, and large language models (LLMs) to solve complex, high-value problems across the enterprise.

This is a unique opportunity to work alongside experts in applied mathematics, statistics, computer science, and physics-collaborating on initiatives that shape the future of MassMutual and the life insurance industry at large.

Overall Responsibilities:

• Architect and lead end-to-end ML/AI solutions s upporting various use cases for a large enterprise using LLMs, deep learning, and probabilistic modeling-from ideation to production .

• Deploy scalable GenAI and Agentic AI systems that directly support business goals.

• Establish and promote best practices in AI development and responsible AI deployment .

• Drive innovation by identifying emerging technologies and translating research into practical applications.

• Collaborate with engineering teams to build robust, production-grade AI pipelines and APIs.

• Prototype and deliver AI-powered applications (e.g., web apps, dashboards, visualizations) that enable data-driven decisions.

• Influence senior leadership by aligning AI initiatives with enterprise strategy and communicating insights effectively.

• Mentor and develop junior talent , fostering a culture of technical excellence and continuous learning.

Candidate Requirements:

• Recognized industry expertise in AI/ML, with a track record of delivering impactful solutions.

• 7+ years of experience in data science, machine learning, or AI engineering roles.

• Deep understanding of machine learning, statistics, NLP, optimization, and LLMs.

• Hands-on experience with AI deployment and orchestration frameworks and protocols (e.g., MLflow , llama-index, MCP ).

• Extensive experience testing LLM behavior across a variety of foundation models and benchmarks.

• Experience building AI-powered applications and collaborating with software engineers and product managers.

• Strong programming skills in Python. Proficiency in R is a plus.

• Proficiency in SQL and database design ; familiarity with cloud-native data platforms , vector databases, and semantic search is a plus.

• Exceptional communication skills , with the ability to explain complex concepts to non-technical stakeholders.

Education:
M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field.