Technical Product Marketing- Principal (AI/ML)

Guidewire Software is the leading platform for Property & Casualty insurers, helping more than 400 carriers worldwide. The AI Technical Product Marketing Principal will drive the positioning and messaging for Guidewire’s AI capabilities, connecting narratives to key offerings and ensuring coherent communication across products and releases.

Responsibilities:

• Define and continuously refine the Guidewire AI story and connect this narrative to key offerings so the field, customers, and partners hear one coherent AI story across products and releases
• Lead audience specific narratives such as:
• CDOs (Data & Governance): Explain Guidewire's P&C data gravity advantage and articulate a clear story on model governance, explainability (XAI), hallucination mitigation, and evaluation
• CIOs (Orchestration & Scale): Position the Agentic Framework/orchestration layer as the governed method for deploying agents, translating architecture (multi-tenant, data residency, isolation, latency, RBAC, observability) into reliability, security, and performance value
• Business Leaders (Claims / Underwriting / Actuarial): Tie AI capabilities to business KPIs (loss/expense ratios, quote turnaround, FNOL handling time, leakage reduction, NPS) to demonstrate how embedded AI delivers faster, better decisions
• Developers & Solution Architects: Define the developer value proposition for the Agentic Framework and tools (APIs, SDKs, Agent Studio) with narratives focused on ease, safety, and speed
• Partner with Product Management and Engineering to turn roadmap and architecture into value‑based narratives, first‑call decks, sales plays, and enablement for customer‑facing teams
• Lead Competitive Positioning: Perform technical teardowns of competitive solutions (horizontal copilots, generic LLM wrappers, and point solutions), contrasting them with Guidewire’s embedded, domain-specific, insurance-grade approach, and maintain sharp competitive positioning and enablement (battlecards, objection-handling guides, POV slides) to help sales and CS teams win AI-influenced deals
• Turn concepts like RAG (retrieval‑augmented generation), tool/agent orchestration, evaluation & testing, knowledge graphs, and policy‑aware routing into accessible, outcome‑oriented stories for technical and executive audiences
• Create high‑credibility assets such as whitepapers, technical briefs, reference architectures, FAQs, social content, and executive decks, explaining how our AI works and why it’s designed that way; support analysts, media, and events with clear narratives and visuals

Requirements:

• AI / Agentic Technical Depth
• 5+ years working directly with AI/ML products or platforms (e.g., LLMs, RAG pipelines, vector stores, agent frameworks, or MLOps/LLMOps tooling)
• Deep understanding of the progression from predictive analytics → generative AI → agentic AI and multi‑agent systems
• Clear, opinionated view on when to use autonomous agents vs. supervised assistants vs. deterministic automation, including appropriate HITL patterns in regulated environments
• Technical & Architectural Fluency
• Comfort explaining concepts such as but not limited to data residency, tenant isolation, observability, inference latency, RBAC, and zero‑trust architectures in business language
• Ability to read and discuss reference architectures and sequence diagrams with engineering, then distill them into simple, visual narratives for executives
• Executive‑Ready Communication
• Proven ability to present to and influence C‑level audiences (CIO, CDO, CTO, business executives), synthesizing technical detail into sharp, defensible points of view
• Strong writing skills across formats: from a one‑page “why now” brief, to a deep‑dive whitepaper, to a launch keynote deck
• Product Marketing Core Skills
• 15+ years in B2B enterprise product marketing, technical marketing, solutions marketing, or adjacent roles, with meaningful time spent on data and/or AI/ML offerings
• Demonstrated experience building messaging, positioning, launch plans, and enablement for technical products, especially those sold to IT and technical buyers
• Hands-on experience with cloud platforms, MLOps / LLMOps, or data platforms (e.g., designing workflows with RAG, vector stores, or orchestration frameworks)
• Hands-on experience partnering with engineering or data science to market/sell AI‑powered capabilities (e.g., retrieval architectures, prompts/guardrails, evaluation frameworks, safety/monitoring pipelines) into production
• Experience launching or supporting AI‑driven features or products in regulated industries (financial services, insurance, healthcare, public sector)
• Ideal candidate has an undergraduate degree in Computer Science, Computer Engineering, &/or Data Science, and hands on development experience in the past