AI Engineer

MassMutual is a leading financial services organization committed to helping individuals and businesses achieve their financial goals through innovative insurance, retirement, and investment solutions. The AI Engineer will work within the Data Science team to design, develop, and deploy AI solutions that influence strategic decision-making and drive business transformation.

Responsibilities:

• Designing, developing, and deploying end-to-end machine learning and AI solutions that support various enterprise use cases, utilizing LLMs, deep learning, and probabilistic modeling from conception through production
• Implementing scalable generative AI (GenAI) and agentic AI systems that align with business objectives and operational needs
• Establishing best practices for AI development, ensuring responsible AI deployment, and adhering to ethical standards and regulatory requirements
• Collaborating with engineering teams to build robust, production-grade AI pipelines, APIs, and infrastructure to facilitate seamless integration and deployment
• Prototyping and delivering AI-powered applications such as web interfaces, dashboards, and visualizations that enable data-driven decision-making across departments
• Evaluating and fine-tuning LLMs and AI agents, managing prompt strategies, and optimizing multi-step workflows for performance and accuracy
• Staying abreast of emerging AI technologies and industry trends, and applying innovative solutions to solve complex business challenges
• Providing technical guidance and mentorship to junior team members and cross-functional partners

Requirements:

• Minimum of 5 years of proficiency in SQL, database design, and familiarity with cloud-native data platforms, vector databases, and semantic search technologies
• Extensive experience in Python programming (5+ years), with proficiency in R considered a plus
• Deep understanding of machine learning algorithms, statistical methods, natural language processing (NLP), optimization techniques, and large language models (LLMs)
• At least 3 years of hands-on experience in data science, machine learning, or AI engineering roles
• Minimum of 2 years of experience working with AI deployment frameworks and orchestration protocols such as agentcore, strands, langchain, MCP, and A2A
• Significant background in developing AI agents and LLM systems, including tool integration, multi-step workflows, retrieval-augmented generation (RAG), prompt management, and evaluating LLM behavior across various models and benchmarks
• Proven experience building AI-powered applications in collaboration with software engineers and product managers
• Hands-on experience with cloud-native development, containerization, and orchestration technologies like Docker and Kubernetes
• Master's degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative discipline