Intelligent Systems Solutions Engineer- Liberty Mutual Investments Technology

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. 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 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 Ability to communicate complex AI concepts to non-technical stakeholders and influence decision-makers with a calm, measured style. Advanced knowledge of agile development methodologies as typically acquired through a Bachelors or Masters 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, Lang Chain or similar orchestration tools, Investments domain exposure; prompt engineering