Technical Product Marketing- Principal (AI/ML)

Guidewire Software is the leading platform for Property & Casualty insurers, helping carriers engage and innovate across the insurance lifecycle. The AI Technical Product Marketing Principal will drive the positioning and messaging for Guidewire’s AI capabilities, ensuring a coherent narrative across products and releases while engaging with various stakeholders to demonstrate the value of AI in insurance.

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