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 solutionssupporting various use cases for a large enterpriseusing 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 identifyingemerging 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.