Senior Software Engineer- AI

Summary Within Guidewire’s Business Technology (BizTech) organization, you’ll join a global team that powers our internal systems and employee experience through secure, scalable platforms and data-driven solutions.

BizTech’s mission is to enable Guidewire’s growth and transformation with innovative, resilient technology, strong governance, and a focus on AI fluency and operational excellence.

You’ll collaborate across engineering, security, and business teams in a culture that values speed, agility, and continuous improvement.

As a Senior Software Engineer – AI, you will design, build, and operate our next-generation AI/ML agent platform and RAG capabilities that support internal teams and, ultimately, the P&C insurers we serve. You will combine deep backend engineering skills with hands-on experience in GenAI, LLM orchestration, and enterprise data integration to deliver secure, production-grade AI services. This is a highly visible role that advances BizTech’s Agentic Platform and GenAI enablement priorities while contributing to Guidewire’s broader mission of transforming the way the world’s P&C insurers do business through cloud, analytics, and AI-powered innovation.

Job Description What you’ll do

• Design, develop, and operate scalable microservices that power the runtime and serving layer for AI/ML agents and RAG components, with an emphasis on reliability, security, and performance.
• Implement and maintain LLM orchestration frameworks (e.g., LangChain, LangGraph, AWS Strands, Google ADK) and integrate them with Guidewire’s core and internal applications to enable robust agent workflows.
• Build and optimize secure data ingestion and indexing pipelines for RAG, leveraging vector databases (such as Pinecone, Weaviate) and graph databases (such as Neo4j) to support complex enterprise use cases.
• Develop secure, scalable data connectors and tool interfaces for systems like Oracle, Salesforce, Workday, and Snowflake, ensuring compliance with data governance and Responsible AI principles.
• Collaborate closely with Security and other stakeholders to embed strong access controls, auditability, and privacy into AI/ML services, balancing innovation with risk management.
• Design and implement automated evaluation frameworks (evals) to measure LLM performance, reliability, and accuracy, and integrate these into CI/CD pipelines for continuous improvement.
• Contribute to BizTech’s Agentic Platform and GenAI enablement roadmap by optimizing engineering workflows (e.g., via coding assistants such as Claude, Cursor, Gemini Code) and championing AI fluency across the team.
• At Guidewire, we foster a culture of curiosity, innovation, and responsible use of AI—empowering our teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes.

What you’ll bring

Required 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.

• 5+ years of professional software engineering experience building backend services or internal platforms, ideally in a cloud-native environment.
• Strong programming skills in Python and/or TypeScript/Node.js for building automation, orchestration, and backend services supporting AI/ML workloads.
• At least 2 years of hands-on experience designing, implementing, and deploying solutions using Generative AI/LLM technologies (e.g., via AWS Bedrock, Google Vertex, or similar).
• Practical experience with LLM orchestration and RAG/agent frameworks (e.g., LangChain, LangGraph, AWS Strands, Google ADK), including tool calling and multi-step workflows.
• Hands-on work with vector databases (such as Pinecone, Weaviate) and graph databases (such as Neo4j), including schema design, indexing strategies, and query optimization.
• Experience integrating LLM-based applications with large-scale, complex enterprise data sources and APIs (e.g., Oracle, Salesforce, Workday, Snowflake).
• Solid understanding of AWS services relevant to AI platforms, including EC2, S3, IAM, and container orchestration (Docker, Kubernetes), plus CI/CD practices for automated deployment of AI/ML services.
• Strong collaboration, communication, and problem-solving skills, with the ability to work across security, data, and business teams in a fast-moving, outcome-oriented environment.

Preferred

• Experience designing MCP (Mo…