Principal Software Engineer – GRS Innovation; Generative AI

you must be authorized to work in the United States without employer sponsorship now or in the future. We will not sponsor employment visas. Candidates who will require future sponsorship, including candidates on CPT/OPT/STEMOPT who will require future sponsorship, are not eligible to apply.

At Liberty, you'll thrive in a hybrid setting that fosters in-person collaboration, innovation and growth. This approach optimizes both remote and in-person interactions, enabling you to connect and ideate with your team and deepen valuable relationships across the company, while still enjoying the flexibility of remote work for focused tasks and projects. This position follows a hybrid work model (2 days onsite) and is open to candidates located in Portsmouth, NH;
Boston, MA;
Plano, TX;
Indianapolis, IN; and Columbus, OH.

• Design and build proofs of concept and initial pilots that apply generative AI to real commercial and specialty insurance problems.
• Develop capabilities involving intelligent document processing, extraction, summarization, question answering, conversational experiences, retrieval-augmented generation, and AI agents.
• Frame hypotheses, define success measures, and use disciplined experimentation to determine whether an idea is valuable, feasible, secure, and scalable.
• Evaluate emerging models, frameworks, and architectural patterns based on evidence rather than novelty.

• Build high-quality reference implementations, reusable components, APIs, integrations, UIs, and automation that application teams can adopt and product ionize.
• Establish clear transition paths through sound architecture, automated testing, deployment guidance, technical documentation, and knowledge transfer.
• Design solutions with security, responsible AI, observability, resiliency, cost, and operational ownership in mind—even when the initial deliverable is a proof of concept.
• Partner with application teams to ensure that experiments can evolve into maintainable, resilient, & secure production solutions without unnecessary rework.

• Partner with architects, technical leads, product owners, and business leaders to clarify needs, surface assumptions, and decompose loosely defined opportunities into testable iterative increments.
• Translate business problems into effective software and architecture decisions, staying current on emerging technologies that can shape Liberty Mutual's approach.
• Balance the speed of learning and generating customer value against enterprise engineering standards and Liberty Mutual's long-term technology direction.
• Recognize when an experiment should advance, change direction, or stop — guided by ongoing communication with customers, the team, and leadership.

• Build trusted relationships with aligned team, peer engineers, architects, data professionals, business partners, and enterprise AI teams.
• Clearly communicate complex technical concepts and recommendations via docs, posts, architecture diagrams, meetings, and similar channels to audiences ranging from hands-on engineers to senior technical or business leaders.
• Mentor teammates and peer engineers through pairing, design reviews, technical guidance, demonstrations, and training.
• Support GRS domain teams attempting their own innovation experiments or implementations.
• Share reusable patterns, lessons, and standards that improve how teams across the organization build and evaluate AI-enabled solutions.

At the Principal level, you will also be expected to shape technical direction across multiple initiatives, influence architecture beyond the immediate team, and increase the effectiveness of engineers and teams through broadly reusable approaches.

• 8+ years of software engineering experience,
  • Hands-on experience designing and building generative AI applications. We're looking for engineers who can build GenAI capabilities and best practices to solve real problems — going beyond engineers who use AI-assisted development tools well.
  • Experience with relevant GenAI techniques and architectures, such as retrieval-augmented generation, agents and tool use, prompt and context engineering, model integration, and structured-output generation.
  • Experience evaluating GenAI solutions for quality, reliability, safety, and business usefulness using repeatable testing and…