Jobs at Guidewire Software

As a Senior AI/ML Platform Engineer, you will architect and scale the ML platform, ensuring efficient ML workflows and collaborating with various teams to drive AI adoption.

Develop and maintain backend features for Guidewire’s application platform and AI services. Build secure, scalable web services using AI coding tools, collaborate on platform operations, write tested code, participate in code reviews, and contribute to AI, cloud, and data platform adoption. Work with LLMs, RAG, vector databases, AI agents, MCP, Kubernetes, and infrastructure as code while supporting continuous improvement and developer experience.

Own the product marketing strategy for Guidewire ClaimCenter, positioning its claims transformation, automation, AI, and workflow capabilities for P&C insurers. Develop messaging, technical content, sales enablement, go-to-market plans, conference presentations, customer workshops, market intelligence, and advocacy programs. Partner with product, engineering, sales, and solution consulting teams to drive adoption, pipeline, and measurable customer business outcomes.

Own the go-to-market strategy, positioning, technical content, sales enablement, thought leadership, and market intelligence for Guidewire’s PricingCenter and Predict products. Translate insurance pricing, predictive modeling, and actuarial workflows into compelling business narratives, influence product roadmaps, support pipeline generation, and engage actuarial and data science leaders at insurers.

Own the product strategy and delivery for data access and integration capabilities within Guidewire’s cloud-native Data Platform. Lead engineering teams from ideation through launch, define requirements and success metrics, guide AI-enabled features, manage integration contracts and dependencies, support customer adoption, and resolve escalations. The role requires strong fluency in AWS security, distributed data systems, streaming, data cataloging, microservices, and emerging AI technologies.

As a Staff Software Engineer on the Data Platform team, you'll architect and develop cloud-native SaaS services, lead distributed systems design, and mentor engineering teams to drive innovative data solutions.

Leads Guidewire’s competitive intelligence program, including competitor monitoring, win/loss analysis, battlecards, executive briefings, sales enablement, and market insight. The role manages a small CI/product marketing team, partners with Product, Strategy, Sales, and GTM leadership, informs product roadmaps, and translates market trends into actionable positioning and strategic narratives.

Design, develop, and maintain Guidewire’s application platform, primarily focusing on backend services, APIs, microservices, and distributed systems. Ensure platform quality, scalability, availability, and security while using AI coding and automation tools. Collaborate across teams, support cloud and data platform adoption, contribute to infrastructure and frontend work as needed, and mentor junior engineers.

Own the architecture and evolution of test automation frameworks for Guidewire Cloud and AI-powered services. Build API, UI, data, contract, and performance automation; integrate testing into CI/CD; and develop AI-driven testing capabilities. Establish standards for distributed, containerized environments using Docker and Kubernetes, improve observability and reliability, define quality objectives, and mentor engineers across teams. The role requires deep expertise in software testing, distributed systems, cloud platforms, and automation architecture.

As an Engineering Manager, you'll lead the Application Platform team, driving innovation in cloud and AI technologies while ensuring secure and scalable solutions for clients. You'll mentor engineers, manage projects, and foster a culture focused on continuous improvement and operational excellence.

Provide technical leadership across multiple engineering teams to design, build, and operate secure, scalable, multi-tenant cloud-native SaaS services. Develop microservices, APIs, automation, and platform capabilities using cloud, container, and IaC technologies; drive AI adoption, ensure reliability, observability, CI/CD, security, and mentor engineers from design through production.

As a Senior Machine Learning Engineer, you will architect a scalable ML platform, collaborate across teams, and ensure best practices for ML workflows and operations.

Designs, operates, and improves cloud and infrastructure security across AWS and multi-cloud environments. Responsibilities include cloud governance, identity and access controls, network security, infrastructure as code, CI/CD and software supply-chain security, container and Kubernetes security, monitoring, threat modeling, incident response, and security automation. The role also contributes to AI security initiatives involving LLMs, AI agents, and MCP integrations, communicates risks across teams, leads complex initiatives, and mentors engineers.

Lead the design, development, deployment, and operation of production-grade generative AI and LLM solutions. Build data and ML pipelines, fine-tune and evaluate models, implement RAG and prompt engineering, and establish MLOps practices on AWS. Drive use cases across insurance workflows, ensure security and responsible AI compliance, mentor engineers, and collaborate with product, engineering, security, finance, and go-to-market teams.

Sell Guidewire’s data and analytics software, particularly the HazardHub geospatial data product, to new and existing P&C insurance customers. Responsibilities include prospecting, relationship management, enterprise sales-cycle leadership, proposals, presentations, competitive analysis, post-sale expansion, trade-show participation, and regular sales reporting. The role requires at least five years of enterprise software sales experience and approximately 25–50% overnight travel for nationwide customer meetings.

Own a defined PolicyCenter product area from customer discovery through launch and adoption. Partner with carriers, engineering, design, field teams, and other product managers to prioritize features, write specifications, manage delivery, address production issues, and measure outcomes. The role focuses on policy administration workflows, underwriting, rating, integrations, cloud delivery, and practical AI capabilities for enterprise P&C insurance customers.

Own a portfolio of Guidewire Analytics clients through onboarding, adoption, value realization, renewals, and expansion. Translate client business challenges into analytics use cases, guide stakeholder engagement, identify retention and growth opportunities, and coordinate internal teams to resolve issues and advance client objectives. The role requires strong client-facing commercial experience, analytical and technical curiosity, consultative problem-solving, and the ability to discuss APIs, datasets, models, and dashboards.

Manages a portfolio of insurance customers by driving adoption, satisfaction, retention, renewals, and expansion of Guidewire solutions. Builds trusted relationships with C-suite, business, and IT stakeholders; develops success and account plans; leads executive reviews; identifies sales opportunities; manages customer health and commercial renewals; advocates for customer needs internally; and mentors other customer success managers.

Leads the transformation of Sales Operations into an AI-first organization by defining strategy, identifying automation opportunities, redesigning workflows, and architecting AI solutions across CRM, data, and enterprise platforms. Designs agents, RAG systems, and intelligent workflows; partners with Engineering and IT on integrations, governance, security, and scalability; establishes evaluation and observability standards; and drives enterprise adoption and executive alignment.

Own go-to-market positioning and marketing strategy for Guidewire PricingCenter and Predict. Develop technical content, sales enablement, thought leadership, and competitive intelligence for actuarial and data science audiences. Partner with product, engineering, and sales to influence the roadmap, accelerate adoption, generate pipeline, and translate insurance pricing, predictive modeling, and machine learning capabilities into compelling business narratives.