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Salary
≈ $22k – $48k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Senior · 5+ years exp
Employment
Full-Time

First seen by Alion on Sep 30, 2026.

Overview
Company
Impact
Profile match
Gainwell Technologies is the nation's leading provider of digital and cloud-enabled solutions across the human services and public health ecosystem. With a mission-driven approach, Gainwell serves clients in all 50 U.S. states, focusing on improving health outcomes and delivering intuitive, human-centered experiences.
Backed by Veritas Capital
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.

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).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.

What We're Looking For

Must-Have

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 hands-on experience with C and Pro*C in Linux/Unix environments; able to read, debug, maintain, and enhance large legacy/brownfield codebases, including embedded SQL, build/make processes, shell scripts, and database interactions.

Strong GitHub fundamentals: branching strategies, PR-based delivery, code reviews, and GitHub Actions (or equivalent CI).Security-minded engineering: familiarity with secure coding practices and integrating automated checks (SAST, dependency scanning, secret detection) into the delivery pipeline.Azure fundamentals for deploying services (App Service/Functions/Container Apps) and secure configuration (Key Vault, RBAC).Ability to convert moderately detailed requirements into clear designs (ADRs/sequence diagrams) and production-ready implementations.

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.Experience with Azure OpenAI, prompt evaluation, and/or RAG (Azure AI Search or equivalent). Data engineering and analytics experience for telemetry pipelines and dashboards (SQL, data modeling, Power BI).

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 from Office - Hyderabad location (5 days)
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