Job Description

What you’ll do

• Lead and grow multiple pods that architect and deliver cloud-native Data Platform services on AWS and Kubernetes, using modern data streaming stacks and a Data Mesh architecture.

• Drive the design and delivery of Gen AI solutions—including MCP servers and agentic services—and build AI-native proficiency across your teams.

• Identify and enable data monetization opportunities, turning platform capabilities into customer-facing, revenue-generating products.

• Partner with product management and engineering leadership to set and deliver quarterly and annual goals, framing problems and defining success metrics.

• Orchestrate cross-functional collaboration across PM, Architecture, SRE/SecOps, Support, and Field Engineering to land features on time and with quality.

• Lead through ambiguity with iterative development: lean discovery, rapid prototyping, A/B and canary rollouts, and telemetry-driven iteration, pivoting quickly on customer feedback.

• Run a rigorous performance management cadence: goals, 1:1s, growth plans, competency rubrics, feedback loops, and fair evaluations.

• Champion engineering best practices: API-first design, SDD, IaC/MLOps, observability, chaos/resilience testing, and data governance.

• Manage execution risk: roadmap and quarterly planning, dependency management, incident postmortems, and proactive risk mitigation.

• Serve as an external evangelist: speak at conferences, panels, and meetups; publish blogs and whitepapers; and partner with Marketing/Comms to strengthen the Guidewire brand.

What you’ll bring

• 16+ years in software engineering with 4+ years managing managers or multi-pod teams building cloud/data platforms.

• Proven delivery of enterprise-scale, cloud-native data platform services at scale (throughput, latency, cost), with a track record of production ownership.

• Hands-on experience building and operating SaaS products, and delivering Gen AI solutions in production (e.g., LLM-based features, MCP servers, RAG, or agentic workflows).

• Experience with data monetization—packaging data and platform capabilities into products that drive measurable business value.

• Strength in product thinking: framing problems, defining success metrics, and shipping iteratively toward outcomes.

• Excellent cross-functional leadership and stakeholder management, with clear written and verbal communication.

• A people leader who coaches for impact, sets high standards, and gives actionable feedback.

• Nice to have: Insurance domain, Analytics/ML pipelines, and data privacy/compliance experience.