You will partner with our AI Architect and Platform Architect to ensure that 4–6 concurrent AI productization projects ship reliably, securely, and at scale, while building a high-performing engineering culture inside the dev pod.
Key Responsibilities
• Team Leadership: Build, grow, and retain a high-performing dev pod of Senior and Consultant Product Engineers, a UI/UX Systems Developer, the QA Dev Architect, and a SecOps Engineer. Own hiring, performance, career development, and team operations.
• Dev-Side Architecture: Hold Architect-level authority for product-side technical decisions — backend architecture, deterministic business logic, database access patterns, and system scaling choices (e.g., RabbitMQ-backed queues, async processing patterns).
• Delivery Oversight: Set the bar for code quality, review standards, and release readiness across all Strike Teams. Day-to-day per-project technical calls are delegated to the SR Product Engineers leading each team; you set the standards they execute against.
• Cross-Pod Coordination: Pair with the AI Architect to ensure deterministic and non-deterministic components compose cleanly. Work with the Platform Architect on shared CI/CD, infrastructure, and observability requirements.
• Stakeholder Alignment: Translate priorities from PS leadership into project commitments, capacity plans, and quarterly roadmaps. Represent the dev pod in regional AI governance forums.
• Hiring & Performance: Drive the hiring pipeline for the open dev-side positions, calibrate leveling, and own performance and growth conversations across your direct reports.
KPIs & Success Metrics
• Product-side workstreams ship on schedule and meet the release-readiness bar across all Strike Teams.
• Code quality and review standards upheld (review coverage, defect escape rate, rework).
• Reliability and scalability targets met for product-side architecture (latency, throughput, uptime).
• Team health and growth: retention, performance calibration, and engineers progressing P2→P3.
• Open dev-side positions filled to plan with calibrated leveling.
Key Skills & Experience
• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
• Experience: 10+ years of software engineering experience, including 3+ years managing engineering teams of 5+ direct reports.
• Technical Proficiency:
– Strong backend development background (Java, Python, or equivalent) with deep experience in system design and distributed systems.
– Hands-on experience with database access patterns, message queues (RabbitMQ, Kafka), and horizontal scaling.
– Working understanding of how AI/LLM features get integrated into production systems. You own the architectural decisions where AI and deterministic components meet, partnering with AI specialists on deeper modeling work and knowing when to bring them in.
– Strong CI/CD and engineering hygiene background (Git workflows, automated testing, observability).
• People Excellence: Track record of building inclusive, high-trust engineering teams, managing performance, and growing engineers from mid-level into senior roles.
• Domain Context: Experience delivering complex enterprise software, ideally in a SaaS or platform productization context.
Preferred Skills & Experience
• Guidewire Knowledge: Prior experience with Guidewire InsuranceSuite or Guidewire Cloud is a significant plus.
• AI Productization: Experience leading teams that ship LLM-powered or AI-assisted features into production.
• Cloud Infrastructure: Familiarity with AWS, container orchestration, and infrastructure-as-code.
• PS Delivery: Background in Professional Services or consulting delivery organizations.