Software Engineer – Generative AI and Documentation Platform

Guidewire Software•San Mateo, CA

1d•$113,000 - $169,000•Hybrid

About The Position

We’re looking for a Software Developer / Senior Software Developer who is excited about building AI-powered content experiences for developers and technical users. In this role, you’ll work at the intersection of generative AI, search, and technical content. You will use modern web, cloud, and data technologies to help shape how developers and customers discover and use our cloud-based P&C insurance platform through trustworthy, AI-powered content experiences. You will help design, build, and evolve our documentation tooling platform, including our AI chatbot, the MCP server, and content ingestion pipelines. You will also work on the tooling and infrastructure that power our content experiences, and improve content creator workflows and publishing performance. If you’ve built chatbots or search experiences over documentation, APIs, or knowledge bases, you’ll feel right at home in this role.

Requirements

Demonstrated ability to embrace AI and apply it to your current role as well as data-driven insights to drive innovation, productivity, and continuous improvement.
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.

Nice To Haves

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Experience with developer/product documentation or other technical content, and an appreciation for information architecture and structured content design.
Exposure to XML, Markdown, or structured content models such as DITA.
Familiarity with cloud platforms (such as AWS) and deploying scalable, secure services.
Experience with observability practices and tools to monitor, troubleshoot, and improve production systems.
Background building tools or automation that improve authoring workflows, content quality, site performance, or documentation search and discovery.

Responsibilities

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.