- Salary
- $120k – $225k
- Location
- Boston, MA, US · Portsmouth, NH, US · Indianapolis, IN, US · Plano, TX, US · Columbus, OH, US
- Workplace
- Remote, Hybrid, Onsite
- Type
- Full-time
- Department
- Engineering
- Seniority
- Lead
- Visa
- Not sponsored
- Closing date
- Today
- Source
- iCIMS
Description
Description
Hiring Manager: Steve Williams
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.
Help shape how generative AI creates value in commercial insurance
Liberty Mutual’s Global Risk Solutions (GRS) business provides commercial and specialty insurance solutions to organizations around the world. Within GRS Innovation, we explore emerging technologies and turn promising ideas into proofs of concept, initial pilots, and reusable engineering patterns.
Our work helps delivery teams solve meaningful business problems while reducing code complexity, testing challenges, and cognitive load. We partner closely with Engineering, Architecture, Data, Analytics, and business teams to determine where emerging capabilities—particularly generative AI—can deliver differentiated value.
Currently, we are advancing designs for an enterprise AI context plane: the patterns and capabilities used to provide AI solutions with relevant, governed, and reusable business context. In addition, the team has been instrumental in developing intelligent document processing capabilities that are central to current and future business-value plans.
We are looking for an inquisitive hands-on engineer who enjoys working at the intersection of experimentation and practical delivery. You will explore ambiguous problem spaces, rapidly asses & test new coding possibilities, and create credible paths from prototype to production.
What you’ll do
Build and validate emerging solutions
- 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.
Create a path from prototype to production
- Build high-quality reference implementations, reusable components, APIs, integrations, UIs, and automation that application teams can adopt and productionize.
- 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.
Navigate complex and ambiguous problems
- 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.
Influence and grow the engineering community
- 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.
Qualifications
What you bring to the team
Experience:
- 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 evaluation practices.
- Strong programming skills in modern languages used for AI and application development, particularly Python and TypeScript/JavaScript.
- Experience with widely adopted AI frameworks, model APIs, vector search technologies, orchestration toolkits, or similar components of the GenAI ecosystem.
- Experience designing APIs, integrations, automation, and reusable software components.
- Experience developing cloud-native applications on AWS or a comparable cloud platform.
- Experience with automated testing, source control, CI/CD pipelines, and modern software-delivery practices.
- Ability to independently structure and advance work when requirements, solution boundaries, or technical approaches are not yet well defined.
- Strong written and verbal communication skills, including the ability to present technical work and recommendations to senior leadership.
Preferred qualifications
- Experience with intelligent document processing, document understanding, multimodal AI, or high-volume unstructured data.
- Experience designing or implementing enterprise context-management, knowledge-retrieval, or data-grounding capabilities for AI applications.
- Familiarity with responsible-AI practices, including data protection, model risk, guardrails, evaluation, traceability, and human oversight.
- Experience mentoring engineers, leading technical communities, or creating technical training and enablement.
- Experience applying emerging technologies in large, regulated enterprises.
- Knowledge of commercial or specialty insurance, particularly complex and high-touch underwriting, claims, or servicing workflows.
How you’ll succeed
You are curious without being driven by novelty. You enjoy moving from an unclear problem to a working solution, but you also know that a successful experiment must produce reliable evidence and a practical adoption path.
You combine hands-on engineering depth with strong judgment and communication. You can build a prototype, challenge its assumptions, explain its tradeoffs to senior leaders, and help an application team understand how to take it forward. You value diverse perspectives and create an environment where teammates can learn, contribute, and do their best work.
If the opportunity interests you but your experience does not align with every preferred qualification, we encourage you to apply. We value relevant capabilities, learning agility, and the potential to make a meaningful impact.
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 evaluation practices.
Education
- A Bachelor’s or Master’s degree in a technical or business discipline, or equivalent experience
Employees may apply for a new role after completing 12 months of employment in their current position.
Employees should review all role requirements and apply only for positions for which they are eligible. Hiring processes may vary by country, including differences in procedures, requirements, and timelines. For country-specific details, please consult your local recruiting / HR team.