Senior Software Engineer, Insurance

About This Opportunity

We are representing a confidential insurtech organization that is building a next-generation insurance platform from the ground up. Our client is reimagining underwriting, policy administration, and claims through AI-first engineering practices. This is a greenfield build on core insurance infrastructure—you'll design and ship services that power quoting, rating, binding, policy lifecycle management, and regulatory compliance.

As a Senior Software Engineer on the insurance platform team, you'll work with agentic AI coding tools as your primary development methodology, not as an experiment. You'll own services end-to-end, make architectural tradeoffs around scaling and reliability, and help build the AI capabilities embedded in the platform itself—from agent-assisted underwriting decisioning to document understanding for policy endorsements.

This is a fully remote role for U.S.-based candidates. Please note that remote work is not available from Alaska, Delaware, Hawaii, Mississippi, Nebraska, Montana, New Hampshire, West Virginia, or the District of Columbia.

Responsibilities

• AI-Native Engineering: Use agentic AI coding tools as your primary development approach for platform builds. Work within team agent configuration patterns, custom skills, and CI/CD integration. Ensure AI-assisted code meets standards: passing CI pipelines, clean pre-commit hooks, and robust evaluations. Apply spec-driven, context-management practices that separate productive AI work from churn.
• Platform AI Capabilities: Build agentic capabilities into the platform itself—agent-assisted configuration, AI-driven underwriting decisioning, document understanding for declarations and endorsements, and conversational interfaces for operations teams. Contribute to RAG pipelines, retrieval, and tool-use patterns grounded in regulated insurance content (rate manuals, underwriting guidelines, state-specific rules). Implement integration patterns (MCP, function calling, structured outputs) that expose platform capabilities to internal agents and external partners. Add observability, evaluation, and cost instrumentation to AI features you own.
• Platform Architecture & Build: Design and build core policy administration services—quoting, rating, binding, issuance, endorsements, renewals, cancellations, and reinstatements. Make well-reasoned design decisions and tradeoffs. Contribute to the rating engine, product configuration layer, and rules framework that enable business teams to launch new states and products without engineering bottlenecks. Implement data models for policy lifecycle, exposure management, and regulatory compliance. Build within event-driven patterns and integration architecture for carrier, vendor, and partner systems.
• Transformation & Migration: Build migration tooling including automated data extraction, transformation, validation, and reconciliation pipelines. Help maintain existing vendor platforms during the transition while building the replacement—context-switching between "keep the lights on" and "build the future."
• Collaboration & Growth: Partner with Product and Insurance subject matter experts to refine requirements and turn domain needs into working software. Participate in design reviews and support teammates through constructive code reviews. Lead by example with strong ownership, accountability, and a high quality bar. This is a hands-on build role—you write production code every week.

What We're Looking For

Required:

• 5+ years of professional software engineering experience building and operating backend services in production
• Demonstrated ability to lead at least one project from conception to production, breaking work into well-tested, reasonably sized releases
• Production-grade engineering depth in Python, Java, or a comparable backend language; comfortable across the stack from data model to API to deployment
• Solid systems design fundamentals: distributed systems, event-driven architecture, API-first design, and data modeling for transactional workloads
• Hands-on experience building LLM-integrated features—RAG, tool use, or agent workflows—running in real software, not just prototypes
• Working familiarity with agentic AI coding tools as part of day-to-day development, with a point of view on what makes AI-assisted work reliable
• Requires minimal direction to deliver in your area; comfortable working in unfamiliar parts of the codebase with guidance
• U.S.-based and able to work core business hours

Strongly Preferred:

• Exposure to homeowners or other personal-lines property and casualty insurance systems, or eagerness to ramp deeply on the domain
• Experience contributing to a custom-built policy administration system, or migration off a legacy/vendor PAS (data migration, parallel-run validation, cutover)
• Experience with AI evaluation, observability for agent runs, prompt and model versioning, or AI cost-management
• Working knowledge of Model Context Protocol (MCP), function calling, structured outputs, and patterns for grounding LLMs in regulated content
• Familiarity with regulatory frameworks: SERFF rate filings, NAIC data calls, state DOI requirements, and the NAIC AI bulletin
• Working knowledge of insurance data standards (ACORD, MISMO) and open-source PCDM data model
• Background in cloud-native infrastructure (GCP preferred), event streaming (Kafka), and modern observability practices
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

How We Work With You

When you apply through Get A Job.ai, a member of our talent team will review your background and schedule an initial screening conversation. If there's a strong match, we'll submit your profile to our client for consideration and guide you through their interview process. Please do not contact the client directly—all communication and interview coordination will flow through Get A Job.ai to ensure a smooth, confidential process.

Pay

Pay via Get A Job.ai has not been disclosed for this role. Compensation details will be discussed during the screening process.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applicants from all backgrounds and evaluate candidates based on skills, experience, and potential.