AI Engineer

MassMutual?s AI & Data Science team is seeking a skilled AI Engineer to join our high-performing, cross-functional team. In this role, you will own the design, development, and delivery of AI solutions that address complex, high-value business problems across the enterprise. You?ll apply machine learning, generative and agentic AI, and LLM-based techniques to real-world challenges, working independently to scope problems, build and evaluate solutions, and bring them into production. At this level, you are expected to take full ownership of defined initiatives with minimal supervision, driving quality and performance from development through deployment.

The Team

This is a unique opportunity to work alongside experts in applied AI, statistics, and computer science. The team operates at the intersection of cutting-edge research and enterprise delivery, building AI solutions that shape the future of MassMutual and the life insurance industry at large. We partner closely with technology and business stakeholders across the organization, and we invest in growth through a culture of peer learning, candid feedback, and shared technical standards. The team is defined by a shared commitment to scientific and engineering excellence, meaningful work, and the kind of collaboration that makes challenging problems tractable.

The Impact

• Design, build, and deliver end-to-end AI/ML solutions for defined business use cases, using LLMs, deep learning, agentic AI, and probabilistic modeling, with ownership of quality and performance from development through deployment.
• Frame and scope AI problems independently, defining success metrics and evaluation criteria in collaboration with stakeholders before and during solution development.
• Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across models, and quantitative analysis, to validate approaches and support sound technical decisions.
• Build rapid prototypes to test AI approaches and advance validated solutions into production-grade applications (e.g., intelligent interfaces, dashboards, automated pipelines).
• Apply best practices in AI development, responsible AI deployment, and production engineering, contributing to team-wide standards and reusable frameworks.
• Communicate findings and recommendations clearly to technical peers and non-technical stakeholders, translating quantitative results into actionable insights.
• Contribute to team knowledge and development, including peer feedback, documentation, and knowledge sharing with less experienced colleagues., * Regular meetings with the AI & Data Science team
• Focused one-on-one meetings with your manager
• Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran and disability-focused Business Resource Groups
• Access to learning content on Degreed and other informational platforms
• Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits

• 4+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering AI/ML solutions independently and at scale.
• 4+ years of experience across the following areas:
• Machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and evaluation of LLM performance across foundation models.
• Building and deploying production AI systems, including model integration, API development, and cloud-based infrastructure.
• Python programming, with the ability to write clean, well-tested, production-quality code.
• Bachelor?s degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field., * Experience with agentic AI frameworks and tooling, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols.
• Breadth across AI and data science methods, including classical ML, causal inference, optimization, and Bayesian approaches, with comfort working across techniques as problems demand.
• Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search.
• Master?s degree or equivalent depth demonstrated through research, applied projects, or prior work. Candidates with a Master?s may be considered with fewer years of professional experience.
• Applied research credentials, such as published work, significant open-source contributions, or a demonstrated record of scientific rigor in industry.
• Clear and effective communication skills, with the ability to explain technical concepts and present findings to both technical and non-technical audiences.