Software Engineer – Generative AI, Documentation Platform

Guidewire Software

. Work with a team of developers to build and enhance the AI chatbot experience for product documentation, from architecture and prototyping through deployment and iteration.

Posted 4/29/2026full-timeSan Mateo • California • 🇺🇸 United StatesMid-LevelSenior💰 $113,000 - $169,000 per yearWebsite

Tech Stack

Tools & technologies

CloudJavaScriptNeo4jNode.jsReactTypeScript

About the role

Key responsibilities & impact

Work with a team of developers to build and enhance the AI chatbot experience for product documentation, from architecture and prototyping through deployment and iteration.
Design, build, and deploy LLM‑powered conversational experiences, including prompt orchestration, tool use, and guardrails.
Develop and operate an MCP server and related tooling that securely exposes documentation, metadata, and internal services as tools/functions for LLMs.
Integrate AI services with our documentation portal, web applications, and backend systems.
Build and maintain ingestion and retrieval pipelines for documentation content (for example, Markdown, DITA, XML, HTML, PDF) to ensure reliable grounding, relevance, and freshness.
Integrate AI services with our documentation portal, web applications, and backend systems.
Develop and maintain APIs and backend services with attention to performance, reliability, and observability.
Design and run evaluation, A/B tests, and telemetry-driven experiments to measure and improve chatbot and content quality, safety, and user experience.
Partner closely with UX and Documentation teams to craft intuitive, trustworthy conversational experiences.
Build and enhance tools and automation that improve content creator workflows and publishing performance.
Contribute across the stack—frontend, backend, and DevOps—to deliver end‑to‑end solutions, working in a modern CI/CD environment.

Requirements

What you’ll need

3+ years of software engineering experience, including 1+ years working on generative AI systems (such as chatbots, RAG-based search, or LLM-driven applications).
Experience with a modern web stack (such as React/TypeScript/Node.js), modern ML/NLP libraries (such as LangChain), and large-language models (LLMs).
Practical experience designing and implementing context-engineering and RAG pipelines, including chunking strategies, embeddings, retrieval, and ranking.
Experience working with vector and/or graph databases (such as Pinecone, Weaviate, or Neo4j) to support semantic search, intelligent recommendations, and knowledge-graph–driven experiences.
Proven ability to design, build, and operate production services and APIs.
Comfort working across the full development lifecycle: design, implementation, testing, deployment, monitoring, and ongoing maintenance in a cloud environment.
Clear, inclusive communication skills and the ability to collaborate effectively with cross-functional partners.

Benefits

Comp & perks

Flexible work environment
Health and Wellness benefits
Paid time off programs including volunteer time off
Market-competitive pay and incentive programs
Continual development and internal career growth opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

software engineeringgenerative AI systemschatbotsRAG-based searchLLM-driven applicationscontext-engineeringRAG pipelineschunking strategiesembeddingsretrieval

Soft Skills

clear communicationinclusive communicationcollaboration