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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Technical Product Manager - AI Integration Organization - **Company:** CoreLogic, Inc. - **Location:** Irvine, CA, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Integration Architecture, Audit Trail, User Authentication, Data Architecture, Metadata, Metadata Standards, Data Streaming, Data Logging, AI Platforms, Virtual Agents, Api Gateway - **Published:** August 10, 2026 - **Apply:** https://www.careerbuilder.com/job-details/principal-technical-product-manager-ai-integration-irvine-ca--ea729b14-90db-47d8-8c2b-48fdd2160f07 ## About the Role API Documentation, Alliance/Partner Marketing, Application Programming Interface (API), Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Authentication, Business Development, Coaching, Cross-Functional, DataArchitect Data Modeling Tool, Documentation, Ecosystems, Insurance, Leadership, MCP - Microsoft Certified Professional, Metadata, Onboarding, Online Publications, Product Demonstration, Product Management, Product Marketing, Real Estate, Risk, Sales/Support Engineering (SE), Standards Development, Technical Leadership, Underwriting ## Description The Principal Technical Product Manager for AI Integration owns the strategy and delivery of Cotality Insurance's external-facing AI integration layer. This includes the MCP server ecosystem, AI/API gateway, developer experience, and the platform that enables AI agents from clients and third-party partners to discover, authenticate, and consume Cotality's insurance data products autonomously. This is a technical product leadership role with a player-coach model. You set the product direction, make architecture tradeoff decisions alongside Architecture, and drive execution through a dedicated engineering team and cross-functional application team partners who own the underlying product APIs. Core Responsibilities MCP Platform Strategy & Roadmap. Define which Cotality data products get exposed as MCP tools, in what order, and with what capabilities. Align the connector roadmap with business priorities across Claims, Underwriting, Catastrophe Risk, and Contractor Solutions. Own the sequencing decisions - what ships this quarter, what's next, and why. Target cadence: one new MCP connector live per month. Tool Schema & Data Product Definition. Partner with product teams and the Data Architect to define what data gets exposed through each MCP tool - the fields, the boundaries, the descriptions that AI agents read to decide when and how to use a tool. This is the highest-leverage work in the role. The quality of tool schemas directly determines whether an AI agent can use Cotality's data effectively or makes errors that damage client trust. Architecture & Technical Direction. Work with the Architect and engineering team to define gateway configurations, authentication flows, and the aggregation layer. Make tradeoff decisions - when to optimize for speed vs. extensibility, when to wrap an existing API vs. build a composite tool, when to ship and iterate vs. get it right the first time. You don't write the code, but you understand the architecture deeply enough to lead technical decisions. Developer Experience. Own the end-to-end experience for external developers and AI platforms integrating with Cotality's MCP endpoints. This includes the developer portal, API documentation, sandbox environments, authentication guides, SDK examples, and onboarding workflows. You understand what good developer experience feels like because you've been the developer - you've integrated against third-party APIs, read bad documentation, and know the difference between a portal that accelerates adoption and one that generates support tickets. Target: a developer or AI agent goes from zero to working Cotality data in under 60 minutes. Data Provenance & Trust. Own the strategy for ensuring data delivered through MCP tools is verifiable, auditable, and resistant to misattribution or hallucination by consuming AI agents. Define response metadata standards, logging requirements, and the guardrails that protect Cotality's brand when data flows through systems Cotality doesn't control. This includes near-term controls (response signing, audit logs, server instructions) and the longer-term innovation roadmap for data provenance. Go-to-Market Coordination. Work with product marketing, sales engineering, and business development to position the MCP platform for carrier clients and AI platform partners. Support demos, pilot programs, and partner integrations. Cross-Functional Execution. Drive delivery through a dedicated MCP engineering team (MCP Architect, MCP ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Resilient by Design: Building Robust Architectures in High-Stakes Financial Systems](https://www.wearedevelopers.com/videos/2106-resilient-by-design-building-robust-architectures-in-high-stakes-financial-systems) - [20 billion requests a week: Upgrading Twilio's API gateway at scale](https://www.wearedevelopers.com/videos/100234-20-billion-requests-a-week-upgrading-twilio-s-api-gateway-at-scale) - [Headless by Design: Building Enterprise Systems That Agents Can Actually Use](https://www.wearedevelopers.com/videos/100092-headless-by-design-building-enterprise-systems-that-agents-can-actually-use) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) ## Related Articles - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)