AI Engineer

Job Description

AI Engineer

Full Time Hybrid (Boston, NYC, Springfield)

The Opportunity

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.

The Team

MassMutual’s Data Science team is seeking an impact-driven AI Engineer to join our high-performing, cross-functional team. In this role, you will develop and deploy 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.

The Impact 

• Develop and deploy end-to-end ML/AI solutions supporting 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. 
• 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. 

Minimum Requirements: 

• 5+ years proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search is a plus.    
• 5+ years skills in Python. Proficiency in R is a plus. 
• 5+ years experience Deep understanding of machine learning, statistics, NLP, optimization, and LLMs. 
• 3+ years of experience in data science, machine learning, or AI engineering roles.   
• 2+ years experience Hands-on with AI deployment and orchestration frameworks and protocols (e.g., agentcore, strands, langchain, MCP, A2A). 
• 2+ years extensive experience and background in AI agents and LLM systems, including tool use, multi-step workflows, RAG, prompt management, and evaluating LLM and agentic behavior across a variety of foundation models and benchmarks. 
• 2+ years experience building AI-powered applications and collaborating with software engineers and product managers. 
• 2+ years experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes 
• M.S. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. 

Ideal Qualifications

• Track record of delivering impactful solutions. 
• Exceptional communication skills, with the ability to explain complex concepts to non-technical stakeholders. 

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