GitHub Copilot Enablement & Productization
Own and evolve an enterprise-ready Copilot enablement approach: usage patterns, prompt standards, and governance for regulated environments.
Create and curate a repository-backed library of reusable prompt files (.github/prompts) for common engineering scenarios (bug fixes, brownfield enhancements from user stories, refactoring, test generation, security remediation).
Guardrails, Security & Quality
Define and implement guardrails so AI-assisted code can’t land without required quality and security signals (tests, reviews, and automated scanning).
Configure and enforce GitHub Advanced Security practices where applicable (CodeQL code scanning, dependency review/alerts, secret scanning/push protection) and integrate results into PR gating.
Establish measurement for AI-assisted development: Copilot usage metrics (suggested vs added LOC, acceptance actions) and repo outcomes (review cycle time, defect inflow proxies, security findings), with clear limitations and directional interpretation.with AppSec and compliance stakeholders to ensure safe handling of sensitive data in prompts, logs, and test artifacts.
.NET Engineering & Platform Integration
Contribute to and review C#/.NET codebases (ASP.NET Core, EF Core) to ensure Copilot guidance and templates match real architecture and patterns.
Build small, maintainable developer tooling and automation (e.g., GitHub Actions, internal utilities, code generators where appropriate) that complements Copilot rather than replacing engineering discipline.
Create and maintain sample reference implementations and ‘golden paths’ that demonstrate secure patterns, test-first fixes, and high-quality PRs.
GenAI Solution Engineering (Supporting)
Develop LLM-powered workflows on Azure (Azure OpenAI) to support developer experience and engineering insights (e.g., PR summarization, guided debugging, quality dashboards).
