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Github Copilot Jobs in Virginia (NOW HIRING)

BTree Solutions, Inc.

GENAI DEVELOPER

Mclean, VA · On-site

GitHub platform + GHCP (Copilot) for engineering workflows * Strong proficiency with GitHub Copilot in day-to-day development. * Deep experience with GitHub platform capabilities: * GitHub Actions ...

CYNET SYSTEMS

Java Full Stack Developer

Arlington, VA · On-site

$55/hr

Hands on experience on GenAI - GitHub Copilot. * Good Understanding on Anthropic AI platform. Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading ...

Koalafi

Technical Lead - DevOps

Arlington, VA · On-site

... GitHub Copilot, Cursor, or equivalent) as first-class parts of the engineering workflow • Own incident response coordination: drive the process, communicate status, and ensure issues reach the ...

Mindlance

Agentic AI Automation Developer

Mclean, VA · On-site

Strong proficiency with GitHub Copilot in day-to-day development. * Deep experience with GitHub platform capabilities: * GitHub Actions (CI/CD pipelines, reusable workflows, composite actions). * PR ...

New

VIS IT Solutions Inc

Java Backend Developer

Ashburn, VA · On-site

$51.75 - $67/hr

Qualifications - Classroom & In-Field Experience with Java 17 or greater. - Familiarity with AI-powered development tools (e.g., GitHub Copilot, AI-assisted debugging) to enhance productivity and ...

CGI Inc.

Mid SW Developer

Fairfax, VA · On-site

Maven/Gradle, Git, IntelliJ/VS Code • Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Amazon Q) • Basic understanding of containerization (Docker) and cloud deployment (AWS ...

eSolutionsFirst, LLC

.Net Developer

Vienna, VA · On-site

$48.50 - $64/hr

Hands-on experience with Claude Code, GitHub Copilot, or equivalent AI coding assistants in production development workflows * Demonstrated ability to prompt LLMs effectively using structured ...

Compunnel

Sr. Software QA Engineer

Mclean, VA · On-site

Exposure to AI-assisted tools for improving test efficiency and coverage (e.g., GitHub Copilot, Microsoft Copilot). * Familiarity with applying AI/ML for test case generation, defect analysis, or ...

System Soft Technologies

Java Developer

Mclean, VA · On-site

$51.75 - $67/hr

Working experience and knowledge of GenAI tools, such as GitHub CoPilot, LLMs, RAG, Agentic AI * Bachelor's degree in computer science or related field.

New

Citizant Inc

DevSecOps Solutions Architect

Haymarket, VA · On-site

$190K - $200K/yr

GitHub Enterprise Server/Cloud, JFrog Artifactory, JFrog Xray, SonarQube, GitHub Advanced Security, GitHub Copilot, and Subject7 * Knowledge of containerization and infrastructure technologies ...

T-Rex Solutions

Senior DevSecOps Engineer

Arlington, VA · Remote

$131K - $180K/yr

GitHub Enterprise Server/Cloud, JFrog Artifactory, JFrog Xray, SonarQube, GitHub Advanced Security, GitHub Copilot, and Subject7 * Knowledge of containerization and infrastructure technologies ...

T-Rex Solutions

Senior DevSecOps Engineer

Arlington, VA · On-site +1

$131K - $180K/yr

GitHub Enterprise Server/Cloud, JFrog Artifactory, JFrog Xray, SonarQube, GitHub Advanced Security, GitHub Copilot, and Subject7 * Knowledge of containerization and infrastructure technologies ...

CYNET SYSTEMS

Integration Architect

Reston, VA · On-site

$70/hr

Leverage GitHub Copilot and AI-assisted tooling to accelerate design, code generation, and integration flow prototyping. * Apply AI acumen to build intelligent mapping engines, automated data ...

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Showing results 21-40

All JobsGithub Copilot JobsGithub Copilot Jobs in Virginia

Github Copilot information

See Virginia salary details

$32.2K

$81K

$124.9K

How much do github copilot jobs pay per year?

As of Jul 24, 2026, the average yearly pay for github copilot in Virginia is $81,049.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,000.00 and $101,100.00 per year, depending on experience, location, and employer.

What is the difference between Github Copilot vs Software Developer?

FeatureGithub CopilotSoftware Developer
Primary RoleAI-powered code completion toolDesigning, coding, testing software applications
Required SkillsProficiency in programming, understanding of AI toolsProgramming languages, problem-solving, software design
Work EnvironmentIntegrated into IDEs, used alongside developersOffice or remote, collaborative or solo coding
CertificationsNone required, but familiarity with coding standards helpsComputer Science degree or coding certifications often preferred

Github Copilot is an AI tool that assists developers by suggesting code snippets, while a Software Developer actively writes, tests, and maintains software applications. Copilot enhances productivity but does not replace the core responsibilities of a developer. Both roles often work together in the software development process.

What are popular job titles related to Github Copilot jobs in Virginia? For Github Copilot jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Github Copilot jobs in Virginia look for? The top searched job categories for Github Copilot jobs in Virginia are:
What cities in Virginia are hiring for Github Copilot jobs? Cities in Virginia with the most Github Copilot job openings:
Github Copilot jobs near you
Infographic showing various Github Copilot job openings in Virginia as of July 2026, with employment types broken down into 34% Full Time, 63% Part Time, and 3% Contract. Highlights an 39% Physical, 1% Hybrid, and 60% Remote job distribution, with an average salary of $81,049 per year, or $39 per hour.
GENAI DEVELOPER

GENAI DEVELOPER

BTree Solutions, Inc.

Mclean, VA • On-site

Contractor

Posted 6 days ago

Job description

Job Title: GENAI DEVELOPER
Location: Mclean,VA
Duration: 12+ Months
Visa: USC, GC, H1B and EAD
Contract Type: W2
JOB DESCRIPTION
1) Agentic test automation foundation (reusable patterns + reference implementations)
  • Design and implement agentic testing patterns that can be adopted by multiple
  • Underwriting teams (and later other domains).
  • Create reference implementations (sample repos / templates) demonstrating:
  • Test generation assistance (from requirements, APIs, contracts, schemas)
  • Test maintenance assistance (auto-updating selectors/contracts, flaky test triage)
  • Failure analysis assistance (root cause suggestions, log correlation, defect drafting)
  • Establish a standard architecture for test code organization, tagging, data management,
  • and execution across UI + API + service layers.

2) Coverage standards, templates, and governance
  • Define and publish coverage standards (what "good" looks like) including:
  • Minimum coverage expectations by service/component
  • Test type mix (unit vs API vs UI vs contract vs integration)
  • Risk-based prioritization and traceability to requirements
  • Provide templates usable across teams:
  • Test plan templates
  • Test case/spec templates (Gherkin-style or equivalent)
  • Definition of Ready / Definition of Done quality checklists
  • Create a scalable tagging/metadata strategy (e.g., feature, service, risk, priority, data
  • sensitivity) to support reporting and quality gates.

3) GenAI-assisted reporting and quality insights across microservices
  • Build automated reporting that aggregates test + service data across multiple
  • microservices, such as:
  • Test execution results (Karate/Playwright + CI runs)
  • Service health signals (logs/metrics/traces if available)
  • Defect signals (issue tracker metadata if available)
  • Generate GenAI-driven summaries:
  • Release readiness narratives
  • Failure clustering and trend analysis
  • Produce outputs consumable by engineering leadership and teams (dashboards,
  • markdown summaries in PRs, artifacts in CI).

4) "Quality gates" via agents
  • Build automated review agents that evaluate user stories/requirements for minimum
  • required clarity and data before development/testing starts:
  • Required fields present (acceptance criteria, testable outcomes, data needs,
  • dependencies)
  • Ambiguity detection and missing edge cases
  • Data/privacy considerations and environment needs
  • Integrate gates into workflow (PR checks, issue templates, GitHub Actions) to reduce churn
  • and rework.

Required Technical Skills (must-have)
  • GenAI / LLM + agentic development
  • Hands-on experience building LLM-powered agents (tool-using, multi-step reasoning, guardrails).
  • Experience with prompting patterns, structured outputs (JSON schemas), evaluation, and reducing hallucinations.
  • Test generation/augmentation
  • Requirements review and completeness validation
  • Report generation and summarization
  • GitHub platform + GHCP (Copilot) for engineering workflows
  • Strong proficiency with GitHub Copilot in day-to-day development.

* Deep experience with GitHub platform capabilities:
  • GitHub Actions (CI/CD pipelines, reusable workflows, composite actions)
  • PR checks, branch protections, CODEOWNERS, templates
  • Automation via GitHub APIs/webhooks (as needed)
  • Test automation engineering (framework expertise)

* Advanced experience designing and implementing automation with:
  • Karate (API testing, contract-like checks, data-driven testing, mocks)
  • Playwright (UI automation, selectors strategy, parallelization, trace/video artifacts)

* Strong understanding of test design and coverage:
  • Happy path scenarios
  • Negative/validation scenarios
  • Edge/boundary scenarios
  • Data setup/teardown strategies and test isolation
  • Cross-service reporting and data aggregation
  • Proven ability to aggregate and normalize results from multiple microservices and multiple pipelines.
  • Experience producing actionable automated reports (trend analysis, failure clustering, service correlation).
  • Automated requirements review agents

* Experience implementing automated checks that validate:
  • Acceptance criteria completeness
  • Required test data and environment dependencies
  • Non-functional requirements (performance, security, observability) when applicable
  • Deliverables / What success looks like (for the posting)
  • A reusable agentic testing automation kit adopted by multiple teams.
  • Published coverage standards + templates and onboarding documentation.
  • A working GenAI-assisted reporting pipeline aggregating results across microservices.
  • Automated quality gates integrated into GitHub workflows that measurably reduce story churn.

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