Maintain healthy code scanner findings and test coverage, and prevent new technical debt.
Set guardrails for agent-generated code and require validation against specifications and standards.
Remove blockers, coach engineers on escalations, validate release timelines, and execute deployments.
Manage technical dependencies within and across teams and improve squad velocity and flow.
Foster a safe environment for questions, experimentation, and reversible mistakes; support team morale and balance.
Model team expectations and deliver direct, constructive feedback.
Join business conversations with the Product Owner to align technical work with outcomes and share knowledge through forums and sessions.
Experience Requirements
7+ years of professional software engineering with solution architecture in complex enterprise environments.
1+ years building GenAI applications, including RAG, agentic search, workflows, and integrations with commercial LLMs.
2+ years leading or mentoring engineers.
2+ years as a senior or principal engineer with design, implementation, and operational ownership.
2+ years leading engineering work in Agile teams with Product Owners, Product Analysts, and Quality Engineers.
Proficiency translating business requirements into technical designs.
Hands-on Python with FastAPI for REST APIs and microservices.
Front-end development with ReactJS.
Building on AWS and Azure, including Azure OpenAI and other LLMs such as Claude.
Designing GenAI and LLM applications for retrieval and synthesis over large document collections.
Systems integration, architecture standards and principles, and SaaS selection and integration.
Elasticsearch development including indexing pipelines, relevancy tuning, and search performance.
CI/CD and DevSecOps, including code quality and security scanning with tools such as SonarQube and Veracode.
Application testing, diagnostics, and performance tuning for a global user base.
Clear technical documentation and architecture artifacts.
Agentic engineering and specification-driven development with reliable AI coding agent execution across the lifecycle while retaining human accountability.
Education Requirements
BA/BS or MS in computer science, information sciences, or a similar field, or equivalent experience.
AWS or Azure cloud certification preferred.