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 (Model Context Protocol) or similar servers for secure tool invocation, data access, and API integration in agentic architectures.

• Prior work implementing or extending automated LLM evaluation frameworks (evals), including test design, metrics selection, and integration into pipelines.

• Familiarity with data governance, Responsible AI practices, and security-by-design approaches for AI/ML systems, especially in regulated or enterprise settings.

• Exposure to observability tooling (logs, metrics, traces) for AI workloads and experience debugging issues across data pipelines, models, and orchestration layers.

• Experience contributing to internal platforms or “citizen developer” tooling that enables broader teams to safely build on AI capabilities, aligned with BizTech’s GenAI enablement goals.

Your Impact

We believe in clarity and setting you up for success. In your first 6 months, you will take ownership of key components of BizTech’s Agentic Platform, stand up or enhance microservices and RAG pipelines in production, and partner with Security to ensure robust controls around enterprise data and AI tools.

You’ll define and implement evals that make LLM performance measurable and trustworthy, while improving engineering workflows through automated tooling and coding assistants. As your work scales, you will help Guidewire become the most efficient, trusted vertical SaaS company by enabling secure, reliable AI agents that enhance employee experiences and accelerate the transformation of how P&C insurers operate.