Software Engineer - AI Platform, Business Technology

Guidewire Software•San Mateo, CA

1d•$109,000 - $186,000

About The Position

BizTech is Guidewire’s internal technology organization, focused on enabling Guidewire’s growth to $2B by delivering innovative, resilient solutions, value‑add services, and excellent employee experiences as “One Global Team.” We emphasize speed, agility, and efficiency, underpinned by a culture of continuous process improvement, data‑driven decision‑making, and balanced risk and controls. You’ll join the AI Platform group, working across cloud, data, security, and application teams to power AI‑enabled workflows for employees worldwide. This Engineer role designs, builds, and operates the core AI platform that gives Guidewire teams secure, reliable access to AI tools, agents, and AI‑powered applications. You will work across the full stack—front‑end, back‑end, and platform services—to deliver production‑ready capabilities that embed AI into everyday work. You’ll partner closely with product, design, Security, and DevSecOps to deliver high‑impact solutions that advance Guidewire’s mission to transform how the world’s P&C insurers do business through cloud, analytics, and AI.

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.
Bachelor’s degree in Computer Science, MIS, or a related technical field (or equivalent work experience) and typically 3+ years of engineering experience building and operating production systems or platforms.
Proficiency in at least one backend language (e.g., Python or Java).
Working experience of AI/LLM/RAG concepts, prompt design, evaluations, and when to use which AI tools and models.
Hands-on experience building and shipping full-stack web applications using modern front-end frameworks (e.g., React, Vue, or Angular) alongside back-end API development in Python or similar languages, with familiarity in relational or NoSQL databases and RESTful or GraphQL API design patterns.
Hands‑on experience with AWS, containers/Kubernetes, and modern DevSecOps tooling such as GitHub, Artifactory, Jenkins, and related CI/CD pipelines.
Practical experience building secure integrations using OAuth, scopes, and policies; comfortable debugging end‑to‑end auth flows and working with Security/Identity teams to resolve issues.
Demonstrated ability to partner with product managers and cross‑functional stakeholders—translating business requirements into technical designs, making trade‑offs explicit, and communicating status and risk succinctly.

Responsibilities

Design, build, and operate core AI platform services that provide a secure, governed access point to AI tools and agents across multiple models and providers (e.g., Anthropic, OpenAI, Google, and internal services).
Design and build AI‑powered, full‑stack applications end‑to‑end—from intuitive React‑based front‑ends to robust back‑end APIs—ensuring seamless integration with AI platform capabilities and a great employee experience.
Collaborate with product and design partners to translate requirements into polished, accessible, and secure production features, using sound engineering judgment in selecting patterns, frameworks, and tools.
Engineer secure integrations across cloud and identity systems (e.g., Okta, SSO, RBAC) using Python or similar languages, partnering closely with Security and DevSecOps to uphold Guidewire’s standards for security and compliance.
Enhance observability and reliability of AI platform components by implementing logging, metrics, tracing, dashboards, and alerting that support incident triage, root‑cause analysis, and continuous improvement.
Participate in BizTech’s tiered AI support model, handling complex, platform‑level issues and novel AI bugs, and feeding runbook, documentation, and tooling improvements back into the system.
Contribute to BizTech’s FY26 priorities by supporting the Agentic Platform architecture, GenAI engineering excellence, and expansion of citizen developer and agent platforms that target growth in AI agent usage.
Mentor and coach associate and mid‑level engineers through design discussions, pairing, and code reviews, helping them apply AI tools (such as coding assistants) and platform standards effectively while raising the overall engineering bar.
Design, deploy, and operate AI-powered workloads on AWS Bedrock AgentCore Runtime, including configuring IAM roles and policies, managing Claude model invocation endpoints, and implementing VPC networking and PrivateLink for secure agent-to-service communication.
Implement multi-step agentic pipelines — defining action groups, managing session state and agent memory, and integrating external tools and APIs.
Build observability and guardrails to handle failure modes such as tool errors, hallucinations, and policy violations at production scale.
Leverage Claude Code as a primary development accelerator — using it for code generation, test authoring, refactoring, and debugging across Python and infrastructure-as-code projects, with proficiency in crafting CLAUDE.md standards and MCP server integrations for automated workflows.
Apply context window management best practices, evaluate model outputs critically, and iterate on prompt strategies to ensure reliability and accuracy in production agentic systems.