Liberty Mutual Investments manages Liberty Mutual Insurance Group’s global financial assets across public and private domains, to create capital and generate income. With over $100 billion in AUM and staffed with 300+ investment, finance and operations professionals located in Boston, MA., Liberty Mutual Investments offers the best of both worlds; the look and feel of a boutique investment firm, and the reputation and financial strength of a Fortune 100 company.

Liberty Mutual Investments Technology (LMI Tech) is actively searching for a Solutions Engineer to work across our organization to design and shape our overall Generative AI strategy. Join a green-field initiative to embed Generative AI across our Investments organization. You’ll be the technical quarterback tracking the fast-moving Gen AI ecosystem, translating capabilities into high-value investment use cases, and leading an engineering pod from whiteboard to production.

Note: This role has a required hybrid work arrangement (3x per week in Boston or NYC).

About the role:

Key responsibilities

• 40% Solution & architecture design: Map LLM/Gen AI capabilities to business needs; craft secure, scalable solution designs and guide the team through reviews and delivery
• 40% Hands-on engineering: Rapidly prototype and code Gen AI proofs-of-concept; contribute production-quality Python (and occasional React) services running on AWS
• 20% Stakeholder & product collaboration: Partner with the Product Owner and Investments stakeholders to refine requirements, set technical direction, and evangelize Gen AI opportunities. Liaise with Compliance, Privacy, and central GenAI teams.

Additional duties

• Continuously scan the Gen AI landscape: model releases, orchestration frameworks, prompt-engineering trends?and assess fit for our roadmap
• Establish engineering standards for code quality, observability, cost-efficient LLM usage, and secure development
• Mentor MLOps engineers and full-stack developers; foster a dynamic, collaborative culture that earns trust across technical and business teams

Highly qualified applicants will have:

• Design of end-to-end solutions as an architect or senior engineer; proven Tech Lead for small, agile teams and the ability to work through others
• Advanced Python skills; experience building services that integrate with LLM APIs (OpenAI preferred).
• Solid understanding of AWS primitives (Lambda/ECS/Fargate, S3, IAM, networking) and secure-by-design principles.
• Comfort with MLOps concepts (model lifecycle, evaluation, monitoring) and CI/CD automation.
• Ability to communicate complex AI concepts to non-technical stakeholders and influence decision-makers with a calm, measured style.
• Nice-to-haves: knowledge of MCP server patterns, React, LangChain or similar orchestration tools, Investments domain exposure

Why join us

• Mission impact: Shape the Gen AI strategy for a highly regulated, high-stakes Investments environment where innovation drives real portfolio value.
• Green-field canvas: Build new capabilities from scratch with executive sponsorship and strong R&D investment.
• Growth & visibility: Own both the architecture vision and the code, interfacing with senior leadership while mentoring a hand-picked team.
• People-centric culture: Collaborative, inclusive, and outcome-focused backed by competitive benefits and work-life balance

If you’re passionate about turning cutting-edge Gen AI into tangible investment insights, and enjoy both coding and architectural leadership, let’s talk. Submit your resume that highlights your experience with Gen AI solutions you’ve designed or built.

• Advanced knowledge of agile development methodologies as typically acquired through a Bachelor`s or Master`s degree in technical or business discipline or equivalent experience
• At least 10 years of related experience
• Design of end-to-end solutions as an architect or senior engineer; proven Tech Lead for small, agile teams and the ability to work through others
• Advanced Python skills; experience building services that integrate with LLM APIs (OpenAI preferred).
• Solid understanding of AWS primitives (Lambda/ECS/Fargate, S3, IAM, networking) and secure-by-design principles.
• Comfort with MLOps concepts (model lifecycle, evaluation, monitoring) and CI/CD automation.
• Ability to communicate complex AI concepts to non-technical stakeholders and influence decision-makers with a calm, measured style.
• Nice-to-haves: knowledge of MCP server patterns, React, LangChain or similar orchestration tools, Investments domain exposure; prompt engineering