Be an Early Applicant
We help people secure their future and protect the ones they love.
The Role
Lead design, deployment, and production scaling of LLM-based and agentic AI systems; evaluate and benchmark models; build prototypes and production AI pipelines; collaborate with engineering and business stakeholders; influence leadership and mentor junior team members.
Summary Generated by Built In
The Opportunity
MassMutual's AI & 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, deployment, and production scaling of advanced AI solutions that solve complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership.
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. This 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
The Minimum Qualifications
The Ideal Qualifications
What to Expect as Part of MassMutual and the Team
#LI-MC
MassMutual is an equal employment opportunity employer. We welcome all persons to apply.
If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need.
California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.
Salary Range: $172,000-$225,700
MassMutual's AI & 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, deployment, and production scaling of advanced AI solutions that solve complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership.
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. This 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
- Architect, build, and lead end-to-end AI solutions supporting a range of enterprise use cases-from ideation through production deployment and monitoring-using LLMs, agentic AI, machine learning, and probabilistic modeling, with accountability for reliability, performance, and maintainability.
- Design and conduct rigorous evaluations of AI system performance, including experimentation, benchmarking across foundation models, and quantitative analysis, to validate approaches and inform technical decisions.
- Drive innovation by identifying emerging technologies, translating cutting-edge research into practical applications, and establishing team-wide best practices in AI development and responsible AI deployment.
- Build rapid prototypes to test and validate AI approaches and deliver production-grade AI-powered applications (e.g., intelligent interfaces, dashboards, automated workflows) when solutions prove viable.
- Collaborate with engineering teams to build robust, production-grade AI pipelines and APIs that integrate into the broader enterprise technology ecosystem.
- Influence senior leadership by aligning AI initiatives with enterprise strategy and communicating complex technical concepts and findings in clear, actionable terms.
- Mentor and develop junior talent, fostering a culture of technical excellence, scientific rigor, and continuous learning across the team.
The Minimum Qualifications
- 7+ years of experience in data science, machine learning, or AI engineering, with a track record of delivering impactful AI/ML solutions at scale.
- Deep expertise in machine learning, statistics, NLP, and LLMs, including generative AI, agentic architectures, prompt engineering, and LLM evaluation across a variety of foundation models and benchmarks.
- Demonstrated ability to build, deploy, and scale production AI systems from architecture planning through orchestration, monitoring, and end-user delivery.
- Strong programming skills in Python, with the ability to write clean, well-tested, production-quality code, including familiarity with Docker, Kubernetes, and other orchestration and deployment frameworks.
- M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field.
The Ideal Qualifications
- Familiarity with agentic AI tooling ecosystems, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols.
- Experience developing and evaluating AI systems in a regulated industry, with a strong understanding of compliance and privacy standards.
- Breadth across AI and data science methods-including classical ML, causal inference, optimization, and Bayesian approaches-with comfort moving across techniques as problems demand.
- Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search.
- Exceptional ability to translate complex AI concepts and quantitative findings into clear insights for non-technical stakeholders and senior leadership.
- Exceptional research credentials, such as published work, significant open-source contributions, or a strong record of scientific rigor applied in industry.
What to Expect as Part of MassMutual and the Team
- 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
#LI-MC
MassMutual is an equal employment opportunity employer. We welcome all persons to apply.
If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need.
California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.
Salary Range: $172,000-$225,700
Skills Required
- 7+ years of experience in data science, machine learning, or AI engineering
- Deep expertise in machine learning, statistics, NLP, and LLMs (including generative AI, agentic architectures, prompt engineering, and LLM evaluation)
- Demonstrated ability to build, deploy, and scale production AI systems (architecture, orchestration, monitoring, end-user delivery)
- Strong programming skills in Python and ability to write production-quality, well-tested code
- Familiarity with Docker, Kubernetes, and other orchestration and deployment frameworks
- M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or related quantitative field
- Familiarity with agentic AI tooling ecosystems (e.g., Bedrock AgentCore, AWS Strands, Azure, MCP/A2A protocols)
- Experience developing and evaluating AI systems in a regulated industry with understanding of compliance and privacy standards
- Breadth across AI and data science methods including classical ML, causal inference, optimization, and Bayesian approaches
- Proficiency in SQL and database design; familiarity with cloud-native data platforms, vector databases, and semantic search
- Ability to translate complex AI concepts and quantitative findings into clear insights for non-technical stakeholders and senior leadership
- Exceptional research credentials (published work, significant open-source contributions, or strong record of scientific rigor applied in industry)
What the Team is Saying
_0.jpeg)
Alex
Customer Communications Technology Director
Asieh
Head of Regulatory HR Technology
Kymberly
Head of Experience Journey Mapping
Jasmine
Head of Data Science - Investments Domain
_0.jpeg)
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Since 1851, MassMutual’s commitment has always been to help people protect their families, support their communities, and help one another. This is why we want to inspire people to Live Mutual. We’re people helping people. Together, we’re stronger.
Why Work With Us
MassMutual has the financial security and stability of a 170+ year old company, with the culture and energy of a startup. We work every day with the customer front of mind to build the best digital experience in the industry.
Gallery
MassMutual Teams
MassMutual Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We believe in capitalizing on the best of being together in our offices as well as personal flexibility. Our workplace philosophy puts office collaboration first, combined with flexibility to work remotely.
Typical time on-site:
3 days a week
