[Hiring] Staff Engineer - Insurance Platform @Porch Group

Role Description

The future is bright for the Porch Group, and we'd love for you to be a part of it as our Staff Engineer, Insurance Platform. Porch is reimagining what it means to be an insurance technology company — and we're doing it from the inside out. As a Staff Engineer on our Insurance Platform team, you'll architect the foundational systems that power how we underwrite, administer, and scale insurance products. We're an AI-first organization, which means you won't just be building for today's requirements — you'll be designing systems intelligent enough to evolve alongside the business. This is a rare greenfield opportunity. You'll bring deep expertise in insurance domain systems — the kind that comes from having built, scaled, or rearchitected complex policy lifecycle platforms — and you'll apply that knowledge to shape something new. If you've ever looked at legacy insurance infrastructure and thought "I know exactly how to do this better," this is your moment.

What You Will Do As A Staff Engineer, Insurance Platform

• AI-Native Engineering — How We Build
  • Use agentic AI coding tools as the primary development methodology for the platform build — not as an experimental side channel.
  • Define agent configuration patterns, custom skills, and CI/CD integration that make AI-assisted development reliable and auditable at production scale.
  • Build evaluation frameworks, quality gates, and pre-commit hooks that ensure agent-generated code meets our standards.
  • Orchestrate multi-agent workflows for parallel feature delivery; lead the team in spec-driven coding, context management, and productive AI-assisted practices.
  • Mentor the broader engineering team on AI-assisted development and evolve those practices as tooling and models advance.
• AI Capability in the Platform — What We Build
  • Architect agentic capabilities directly into the platform: agent-assisted configuration, AI-driven underwriting decisioning, automated document understanding for declarations and endorsements, and conversational interfaces for the operations team.
  • Design RAG pipelines, retrieval architectures, and tool-use patterns that ground LLM behavior in regulated insurance content (rate manuals, underwriting guidelines, state-specific rules).
  • Define integration patterns (MCP, function calling, structured outputs) that expose platform capabilities cleanly to internal agents and external partners.
  • Establish AI observability, evaluation, and cost-management frameworks so production agent behavior is measurable, debuggable, and bounded.
  • Set responsible-AI guardrails that keep agent-influenced decisions auditable and aligned with insurance regulatory requirements (NAIC AI bulletin, state DOI expectations).
• Platform Architecture & Build
  • Design and build core PAS services: quoting, rating, binding, issuance, endorsements, renewals, cancellations, and reinstatements.
  • Own the technical architecture for a modular, API-first platform supporting multi-state, multi-carrier homeowners insurance.
  • Build the rating engine, product configuration layer, and rules framework that allow business teams to launch new states and products without engineering bottlenecks.
  • Define data models for policy lifecycle, exposure management, and regulatory compliance (bureau reporting, NAIC data submissions, state filing requirements).
  • Establish event-driven patterns and integration architecture for the dozen-plus carrier, vendor, and partner systems the platform must connect with.
• Transformation & Migration
  • Lead the engineering strategy to migrate off existing vendor PAS platforms onto our custom-built platform.
  • Design migration tooling: automated data extraction, transformation, validation, and reconciliation pipelines.
  • Run shadow comparisons of new platform output against incumbent systems before each cutover.
  • Maintain production stability on existing platforms while simultaneously building the replacement.
• Technical Leadership
  • Partner with the Director of Insurance Engineering, Product, and Insurance SMEs to translate domain requirements into platform capability.
  • Set engineering standards, lead design reviews, and serve as the technical authority on architecture decisions for the platform build.
  • Stay hands-on — this is not a whiteboard architect role; you write production code.

Qualifications

• 10+ years of professional software engineering experience, with at least 3 years at a Staff or Principal level influencing engineering organizations of 30+ engineers and partnering with technical executives to set multi-year technical strategy in the insurance domain.
• Homeowners or other personal-lines P&C domain depth; auto and home strongly preferred.
• Directly responsible for designing, building, and operating a custom-built P&C policy administration system in production — not configuring or implementing a vendor platform.
• Demonstrated ownership of a PAS transformation or migration: leading the move from a legacy or vendor system to a custom-built platform, including data migration, parallel-run validation, and operational cutover.
• Production experience shipping LLM-integrated systems — RAG pipelines, agent workflows, tool-use patterns, or other agentic capabilities running at real scale.
• Hands-on experience using agentic AI coding tools as a primary development methodology, with a working point of view on agent configuration, custom skills, and evaluation patterns.
• Strong systems design fundamentals: distributed systems, event-driven architecture, API-first design, data modeling for transactional and regulatory workloads.
• Production-grade engineering depth in Python, Java, or a comparable backend language; comfortable across the stack from data model to API to deployment.
• Demonstrated ownership of a multi-quarter platform initiative end-to-end — from architecture through delivery.
• US-based; able to work core business hours.

Strongly Preferred

• Experience leading a multi-state or multi-product rollout on a custom-built insurance platform.
• Experience designing AI evaluation frameworks, observability for agent runs, prompt and model versioning, and AI cost-management at production scale.
• Working knowledge of Model Context Protocol (MCP), function calling, structured outputs, and practical patterns for grounding LLMs in regulated content.
• Familiarity with regulatory frameworks: SERFF rate filings, NAIC data calls, state DOI requirements, and emerging responsible-AI standards.
• Working knowledge of insurance data standards (ACORD, MISMO) and the 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.

Benefits

• Pay Range*: $187,500 - $237,500 annually.
• Eligibility for long-term incentive awards, subject to program guidelines and approvals.
• Annual bonus based on individual and company performance, subject to program guidelines and approvals.
• Comprehensive healthcare benefits including three (3) Medical plan options, two (2) Dental plan options, and a Vision plan.
• Voluntary plans for Critical Illness, Hospital Indemnity, and Accident.
• Pre-tax savings options including a partially employer funded Health Savings Account and employee Flexible Savings Accounts.
• Company paid Basic Life and AD&D, Short and Long-Term Disability benefits.
• Traditional and Roth 401(k) plans available with a discretionary employer match.
• Supportlinc for mental health and wellbeing resources.
• LifeBalance for year-round discounts on various services.
• Wellness programs including flexible paid vacation, company-paid holidays, paid sick time, paid parental leave, identity theft program, travel assistance, and fitness discounts.