Head of Product Security
Exodus
CloudSDLC
Product Manager- GenAI & ML/AI
Guidewire Software
full-time
Posted on:
Origin: • 🇺🇸 United States
Visit company websiteSalary
💰 $138,000 - $245,000 per year
Job Level
Mid-LevelSenior
Tech Stack
CloudGuidewireMicroservices
About the role
- Our Underwriting Solutions guild is taking a bold step forward: we are building Guidewire’s first AI‑native application from the ground up; a fully digital submission state machine that carries risks seamlessly from new to renewal with unmatched speed, accuracy, and minimal human touchpoints.\n
- This initiative leverages every component in our cloud and AI platform and aims at leveraging the latest technology to provide the backbone and flexibility insurers need to digitize their processes and design e2e underwriting workflows.\n
- To help us deliver on this vision, we are looking for a Product Manager (PM or Sr PM, depending on experience) who can bring hands on, technically fluent leadership across data science best practices around data ingestion, extraction, risk assessment and platform integration.\n
- What we value: Growth mindset and curiosity - you ask “why” until the root cause and problem statement are clear and you are eager to explore emerging ML and LLM methods to disrupt the current status quo.\n
- Hands on problem solver – When issues arise, you partner with the pod to debug rather than merely escalate.\n
- Technical fluency - you are comfortable white boarding user flows, detailing the jobs to be done as well as having a microservices mentality and knowledge of available platform components we can build an app with.\n
- Business Empathy – You can explain complex model trade‑offs as it relates to user and business needs and you are naturally curious to engage with customers and gather feedback on solutions.\n
- Adaptive Tenacity - You thrive in ambiguity and can chart a path forward under any circumstance.\n
- Job Description Key Responsibilities Customer discovery and research: Customer first and research mentality where you will work closely with underwriters and UX/Research to uncover high-impact problems and frame scalable solutions ensuring our solutions solve real UW pain points and bring in that knowledge into our development and ML teams for design and prioritization.\n
- Data science and AI expertise: Bring hands‑on expertise in ML, LLMs, prompt design, retrieval‑augmented generation, design AI agents per use case and LOB tasks, evaluation loops and guide the ML team in selecting models, tuning workflows, and measuring performance to improve performance.\n
- Delivery and execution: partner closely with engineering pods on the day to day execution of prompt design, ingestion workflows and extraction capabilities across file types (xls, csv, pdfs, ACORD forms, slips, etc).\n
- Drive the development of products and solutions that make this data easily consumable by other agents deployed in other areas of the UW solutions application focusing on enabling consumption and seamless automation of this data with other downstream products.\n
- Metrics and iteration: define evaluation frameworks across tools. Champion rapid experimentation when results fall short and communicate KPIs broadly across teams as well as leanings that may help other teams as well as developing a framework for measuring usability and success of each feature released to customers that can be tied to value.\n
- Platform translation: Become deeply fluent in Platform building blocks and act as the translation between technical teams and business stakeholders, ensuring every feature advances our vision and delivers customer value.
Requirements
- 3–7 years building B2B SaaS or data products, with 2+ years directly responsible for ML or LLM features.\n
- Experience in prompt engineering, building evaluation frameworks.\n
- Prior exposure to insurance core system integrations (e.g. InsuranceSuite ) is highly desirable.\n
- Insurance domain knowledge particularly in Commercial Lines insurance, including cyber, property, and liability (or a hunger to learn the domain fast).\n
- Experience with user research, data driven prioritization and roadmap development.\n
- Bonus Experience Practical experience with data labeling pipelines and model evaluation frameworks.\n
- Experience using RAG, LangChain, SageMaker or similar tech.\n
- Experience building AI agents, MCP servers or ML models and ability to defend the best solution depending on the problem at hand.
