Gen AI Engineer (C/Pro*C with GitHub Copilot)

Summary 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 C and Pro*C delivery workflows in Linux/Unix-based legacy environments, 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.This role is strictly involved in development of product 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 product development and does not include handling or processing of sensitive health or personal information.

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).Author and maintain custom instruction files (repository and organization patterns) to enforce coding standards, architecture conventions, error handling, logging, and testing practices.Design interactive ‘guided’ prompts that ask one question at a time, minimize friction for low adopters, and require user confirmation before applying code changes.Collaborate with teams to integrate Copilot into day-to-day workflows in Visual Studio and GitHub (PR templates, checklists, review guidance). 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). 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. Partner with AppSec and compliance stakeholders to ensure safe handling of sensitive data in prompts, logs, and test artifacts. C / Pro*C Engineering & Legacy Platform Integration:Contribute to and review C and Pro*C codebases, including embedded SQL and database interaction patterns, to ensure Copilot guidance and templates align with real legacy architecture, coding conventions, and production behavior. Work confidently in Linux and Unix environments, including shell commands/scripts, build and make processes, compilation/linking, runtime diagnostics, log analysis, and batch/job execution. Analyze, debug, maintain, and enhance large brownfield and legacy codebases with limited documentation; trace dependencies and data flows across C/Pro*C modules, scripts, database objects, and interfaces while preserving existing behavior. 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). Implement prompt contracts, tool/function calling patterns, and evaluation harnesses for reliability, cost, and safety. Where needed, build retrieval-augmented generation (RAG) pipelines and connectors to enterprise knowledge sources with grounding/citations.