Job Description
End-to-End Feature Delivery: Own the dev work on a Strike Team — REST APIs, frontend wiring, feature logic, and integration with AI components — for one high-complexity or strategic AI productization project at a time.
Technical Execution: Make day-to-day implementation calls, contribute to design reviews, and make sound trade-off decisions on your features; escalate cross-cutting concerns to the Engineering Manager.
AI Integration: Partner with your AI Engineer to bring LLM-based components into production paths — prompt invocation, response handling, fallbacks, observability. You'll shape how these components are integrated, collaborate on the design decisions that affect the product, and bring the AI Architect in on the deeper algorithmic calls.
Platform & Standards Consumption: Build on top of the team’s d CI/CD, vector DB, auth, QA, and UI/UX foundations. Push back to the horizontal layer when something is missing or wrong.
Code Quality & Mentorship: Set a high bar for code review, testing, and engineering hygiene through your own work. Mentor the Consultant Product Engineer and the AI pairing partners.
AI-Native Development: Leverage AI coding tools (Claude Code, Copilot) to accelerate delivery while maintaining a high quality bar.
KPIs & Success Metrics
End-to-end delivery of high-complexity or strategic projects on schedule.
Quality bar upheld: review standards, test coverage, and observability for owned features.
Reliable AI integration — LLM-backed paths with sound fallbacks and acceptable latency.
Mentorship impact: growth of the Consultant Product Engineer and AI pairing partners.
Platform feedback loop: gaps surfaced and resolved with the horizontal teams.
Key Skills & Experience
Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
Experience: 8+ years of software engineering experience, with a strong focus on backend or full-stack production development.
Technical Proficiency:
– Expert-level skills in at least one production backend language (Java, Python, or TypeScript) and the surrounding ecosystem.
– Strong REST API design experience, database modeling (SQL and at least one NoSQL store), and event-driven patterns.
– Working knowledge of frontend frameworks (React or equivalent) sufficient to wire UI components into your APIs.
– Working understanding of LLM APIs and how AI features are integrated — prompt invocation, streaming, retries, fallbacks. You'll partner with AI specialists on the modeling and data-science work, contributing to the integration design and knowing when to bring in the AI Architect.
– Experience with coding assistants (Claude Code, Copilot).
Engineering Excellence: Track record of shipping production features end-to-end. Strong CI/CD, Git workflow, automated testing, and observability habits.
Domain Context: (Preferred) Experience with enterprise software, regulated industries, or multi-tenant SaaS.
Preferred Skills & Experience
Cloud Infrastructure: Hands-on AWS experience (Lambda, ECS, API Gateway, RDS).
AI Productization: Experience shipping LLM-powered or RAG-based features into production.
Guidewire Knowledge: Prior experience with Guidewire InsuranceSuite or Guidewire Cloud is a significant plus.
Team Leadership: Prior experience leading small teams or owning a feature area end-to-end.
