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Genai Developer Jobs in Washington, DC (NOW HIRING)

BTree Solutions, Inc.

GENAI DEVELOPER

Mclean, VA · On-site

GENAI DEVELOPER Location: Mclean,VA Duration: 12+ Months Visa: USC, GC, H1B and EAD Contract Type: W2 1) Agentic test automation foundation (reusable patterns + reference implementations) * Design ...

Sentrillion

GenAI Developer

Ashburn, VA · On-site

Recruiting for GenAI Developer experience to join our team in our Ashburn VA facility. This is a flexible onsite position. Must be able to report to the office as required. * Design, develop, and ...

Sentrillion

GenAI Developer

Reston, VA · On-site

$115K - $195K/yr

Recruiting for GenAI Developer experience to join our team in our Ashburn VA facility. This is a flexible onsite position. Must be able to report to the office as required.Design, develop, and ...

Brooksource

GenAI Developer

Mclean, VA · On-site

$65 - $75/hr

GenAI Developer Location: DMV Area (Washington, DC, Maryland, Virginia) Hybrid Role - 1-2 days/wk Compensation: $65 - $75/hr (Depending on skillset, experience, and clearance) ABOUT THE ROLE Join a ...

New

Xenith Solutions LLC

GenAI Developer

Leesburg, VA · On-site +1

$115K - $165K/yr

Xenith Solutions is seeking a GenAI Developer with agile methodology experience to join our team in support of a Customs and Border Protection (CBP) contract. As a member of the team, you will ...

Sentrillion

GenAI Developer

Reston, VA · On-site

$115K - $195K/yr

Recruiting for GenAI Developer experience to join our team in our Ashburn VA facility. This is a flexible onsite position. Must be able to report to the office as required. * Design, develop, and ...

Xenith Solutions

GenAI Developer

Leesburg, VA · Remote

$115K - $165K/yr

Xenith Solutions is seeking a GenAI Developer with agile methodology experience to join our team in support of a Customs and Border Protection (CBP) contract. As a member of the team, you will ...

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Genai Developer information

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How much do genai developer jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for genai developer in Washington, DC is $59.62, according to ZipRecruiter salary data. Most workers in this role earn between $45.58 and $72.98 per hour, depending on experience, location, and employer.

What is a GenAI developer?

GenAI Developers are professionals who design, build, and optimize applications using generative artificial intelligence technologies. They work with models such as GPT, DALL-E, or Stable Diffusion to create tools for generating text, images, code, and other content. These developers need strong programming skills, a solid understanding of machine learning, and experience working with AI frameworks and APIs. Their responsibilities often include training custom models, integrating AI into products, and ensuring ethical use of generative AI solutions.

What are some common challenges GenAI developers face when integrating generative AI models into existing products?

GenAI Developers often encounter challenges related to model deployment, scalability, and ensuring data privacy when integrating generative AI models into established products. Balancing the computational requirements of large AI models with real-time application demands can be complex, and optimizing inference speed without sacrificing model quality is a key consideration. Additionally, collaborating closely with product managers, data scientists, and DevOps teams is essential to align AI outputs with business goals and maintain robust, ethical AI practices.

What are the key skills and qualifications needed to thrive as a GenAI developer, and why are they important?

To thrive as a GenAI Developer, you need a strong background in machine learning, deep learning frameworks (like TensorFlow or PyTorch), and programming languages such as Python, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (AWS, Azure, GCP), APIs, and prompt engineering, as well as certifications in AI or ML, are typically used in this role. Creativity, problem-solving, and effective communication set outstanding GenAI Developers apart. These skills are crucial for building, optimizing, and deploying powerful generative AI models that address complex business challenges.

What is the difference between Genai Developer vs Machine Learning Engineer?

AspectGenai DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with NLP and AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming and ML skills
Work EnvironmentDevelops AI models focused on generative AI, often in AI startups or tech companiesBuilds and deploys ML models across various industries, including tech, finance, healthcare
Employer & Industry UsagePrimarily in AI-focused companies, research labs, and tech firmsWidely used across industries like tech, finance, healthcare, and retail

While both roles involve AI and machine learning, Genai Developers specialize in creating generative AI models like chatbots and content generators, whereas Machine Learning Engineers develop a broader range of ML models for various applications. The roles overlap in skills and tools but differ in focus and industry applications.

How to become a GenAI developer?

To become a GenAI developer, you should gain expertise in machine learning, deep learning, and natural language processing, with a focus on generative models like GPT. Proficiency in programming languages such as Python, experience with frameworks like TensorFlow or PyTorch, and understanding of large language models are essential. Building a portfolio of projects and staying updated with AI research can also enhance your qualifications.

Is a Genai Developer a promising career?

A Genai Developer is a growing role focused on developing and implementing generative AI models, which are increasingly used across industries. The field requires skills in machine learning, programming, and AI frameworks, and offers strong job growth prospects due to expanding AI adoption. Continuous learning and staying updated with new tools are important for success in this career.
Genai Developer jobs near you
Infographic showing various Genai Developer job openings in Washington, DC as of August 2026, with employment types broken down into 82% Full Time, 4% Part Time, and 14% Contract. Highlights an 81% Physical, 6% Hybrid, and 13% Remote job distribution, with an average salary of $124,011 per year, or $59.6 per hour.

GENAI DEVELOPER

BTree Solutions, Inc.

Mclean, VA • On-site

Contractor

Re-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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