Senior Software Engineer - Legal & Compliance (AI)

About the role

Who Are We? Taking care of our customers, our communities and each other. That's the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it. Job Category Technology Compensation Overview The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance-based cash incentive awards. Salary Range $139,400.00 - $230,000.00 Target Openings 1 What Is the Opportunity? Travelers is seeking a Senior Software Engineer to join our Corporate Technology - Legal & Compliance organization as we grow and transform our Business Delivery and Technical landscape. As a Senior Software Engineer you will drive our ability to provide advanced and modernized technical solutions to our business partners. In this role, you will design, build and support technical solutions with a primary focus on designing and delivery of GenAI solutions. This role will be responsible for best practice guidance and technical guidance of engineering peers. What Will You Do? Familiarity with AI use cases common to Legal and Compliance environments - contract analysis, eDiscovery, legal hold automation, regulatory research, and policy Q&A Advances and aligns the teams to enterprise standards and practices (AWS tag compliance, Semantic Versioning, API Governance compliance, Source code management, TDD, Code quality checks, Dependency management, Security and secrets management, Site reliability engineering) Implements and expands test automation providing direction and input into overall quality needs Demonstrates asset ownership and leadership of operational excellence Leads stakeholder conversations with partnership and understanding of business problems Communicates effectively and concisely with all team members and describes technology concepts in ways the business can understand their value Identifies learning opportunities and needs in connection with strategic imperatives for team members Take the lead on directing and implementing solutions to moderately complex, loosely scoped problems that are aligned with team goals. Deliver efforts both independently and by leading other team members. Lead investigation and resolution efforts for critical, high impact problems, defects, and incidents. Act as a technology advocate, independently seeking opportunities where technology can be utilized to improve the business. Provide technical guidance and mentorship while fostering a team environment. Apply knowledge of current industry trends and techniques to formulate solutions within the context of assigned efforts. Seek opportunities to expand technical knowledge and capabilities. Perform other duties as assigned. What Will Our Ideal Candidate Have? Hands-on experience building and deploying AI solutions end-to-end, including model integration, prompt engineering, RAG (Retrieval-Augmented Generation) architectures, and LLM orchestration frameworks (LangChain, LlamaIndex, or similar) Proficiency with AWS services commonly used in AI workloads - Bedrock, SageMaker, Lambda, S3, Step Functions, and API Gateway - to build scalable, event-driven AI solutions Proficiency with AI model APIs and SDKs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock) and experience evaluating, fine-tuning, or adapting foundation models for domain-specific use cases Experience designing and implementing AI agent workflows, including tool use, memory management, and multi-step reasoning patterns Ability to instrument AI systems with observability tooling to track model performance, drift, token costs, latency, and output quality in production Familiarity with prompt versioning, evaluation frameworks, and A/B testing strategies specific to generative AI systems Experience integrating AI capabilities into existing enterprise platforms and workflows (document management systems, case management tools, workflow automation) via APIs and microservices Deep understanding of data privacy and security controls specific to AI systems, including PII detection and masking, input/output filtering, and access-controlled knowledge bases Awareness of emerging AI governance frameworks and enterprise AI policy requirements, with the ability to build guardrails and audit trails into AI solutions from the ground up Proven record of collaborating on technical solutions with varying levels of engineers and technical k