Summary
This role is strictly involved in business analysis, requirements documentation, and healthcare reference data support activities and does not involve direct access to Protected Health Information (PHI), Personally Identifiable Information (PII), or any secured or confidential client data. The work is limited to analysis of healthcare claims, reference code sets, and system configurations using governed datasets and does not include handling or processing of sensitive health or personal information.
We’re seeking a hands-on engineer to accelerate developer productivity and engineering quality by operationalizing GitHub Copilot (Business/Enterprise) across the SDLC, with a strong focus on secure, governed adoption. You will design and maintain Copilot customization assets (prompt files, custom instructions, reusable agents) for common .NET delivery workflows, and build supporting GenAI services on Azure where needed. You will partner with platform engineering, security, and product teams to define guardrails, measure impact (productivity, quality, and risk), and continuously improve developer experience.
Your role in our mission
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).
What we're looking for
5–7 years of software engineering experience delivering production systems with strong engineering discipline (testing, reviews, CI/CD).
Hands-on experience using GitHub Copilot in professional development workflows; ability to design and operationalize prompt files, custom instructions, and reusable agent-like workflows for teams.
Practical experience with .NET (C#) and modern application development (ASP.NET Core and/or EF Core); able to read, debug, and implement changes confidently.
Strong GitHub fundamentals: branching strategies, PR-based delivery, code reviews, and GitHub Actions (or equivalent CI).
Nice-to-Have
GitHub Copilot administration experience (policy management, organizational customization, adoption measurement and reporting).
Experience building developer tooling or IDE extensions (Visual Studio/VS Code), internal CLIs, or PR automation.
Hands-on with GitHub Advanced Security (CodeQL, secret scanning, dependency review/Dependabot) and rulesets/required checks for merge gating.
Core Competencies
System Design: clear, scalable architecture with documented trade-offs.
Code Quality: readable, tested, maintainable code with robust error handling.
What you should expect in this role
Copilot customization assets (prompts/instructions/workflows) that materially improve cycle time and developer experience without compromising quality or security.
Clear, trustworthy reporting of Copilot adoption and impact, including known limitations of telemetry and measurement.
Reduced friction for common work (small fixes, bug triage, test creation) through repeatable Copilot-guided workflows that keep developers in control.
Well-governed, secure AI-assisted development practices aligned with enterprise standards.
Work Mode - Remote Opportunity
