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Contract Llm Developer Jobs in Virginia (NOW HIRING)

BTree Solutions, Inc.

GENAI DEVELOPER

Mclean, VA · On-site

USC, GC, H1B and EAD Contract Type: W2 1) Agentic test automation foundation (reusable patterns ... GenAI / LLM + agentic development * Hands-on experience building LLM-powered agents (tool-using ...

Halvik

Jr. BI Developer

Vienna, VA · On-site

$85K - $95K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals ... Use approved AI/LLM tools to accelerate SQL writing, documentation, data exploration, and ...

PB consulting

GenAI Test Automation Engineer

Alexandria, VA · On-site

$44.50 - $58.75/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Merrifield, VA · On-site

$46 - $60.50/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Ashburn, VA · On-site

$47 - $62/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Oakton, VA · On-site

$46.75 - $61.50/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Greenway, VA · On-site

$37.75 - $49.75/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Herndon, VA · On-site

$47.25 - $62.50/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Dulles, VA · On-site

$45.50 - $60.25/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Burke, VA · On-site

$45.50 - $60/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Vienna, VA · On-site

$46.25 - $61/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Clifton, VA · On-site

$41.75 - $55.25/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

PB consulting

GenAI Test Automation Engineer

Fairfax, VA · On-site

$47 - $62/hr

Hands-on experience building LLM-powered agents and agentic workflows. * Experience using ... Karate (API testing, contract testing, data-driven testing) * Playwright (UI automation, selectors ...

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All JobsContract Llm Developer JobsContract Llm Developer Jobs in Virginia

Contract Llm Developer information

What is a contract LLM developer?

Contract LLM Developers are professionals hired on a temporary or project basis to design, develop, and implement applications using large language models (LLMs) like GPT-4. They typically work with organizations seeking to integrate advanced natural language processing (NLP) capabilities into their products or services. Contract LLM Developers are skilled in machine learning, programming languages such as Python, and have experience with AI frameworks and APIs. Their responsibilities may include fine-tuning language models, building conversational AI systems, and ensuring the ethical use of AI technologies.

What are the key skills and qualifications needed to thrive as a contract LLM developer?

To thrive as a Contract LLM Developer, you need strong programming skills (often in Python), a solid understanding of machine learning concepts, and experience with large language models, typically supported by a degree in computer science or related field. Familiarity with tools like TensorFlow, PyTorch, Hugging Face Transformers, and cloud platforms, as well as experience with APIs and version control systems, is common. Excellent problem-solving, communication, and the ability to quickly adapt to new technologies help you stand out in this freelance or project-based role. These skills are critical for efficiently developing, fine-tuning, and deploying sophisticated language models that meet client requirements.

What are some common challenges contract LLM developers face when working with clients on AI projects?

Contract LLM Developers often encounter challenges such as aligning client expectations with the current capabilities and limitations of large language models, ensuring data privacy and compliance, and integrating AI solutions into existing systems. Communication is key, as clients may not fully understand the technical constraints or required data preparation. Additionally, managing project scope and timelines while balancing multiple stakeholders' input can require strong project management and negotiation skills.

What is the difference between Contract Llm Developer vs Contract Software Engineer?

AspectContract Llm DeveloperContract Software Engineer
Required CredentialsTypically requires a law degree, LLM specialization, and legal certificationsRequires a computer science degree or related technical certifications
Work EnvironmentLegal firms, AI companies focusing on legal tech, or law departmentsTech companies, software development firms, or startups
Industry UsageLegal tech, AI legal applications, compliance toolsGeneral software development, AI, and tech industries
Common Search/ComparisonYesYes

The Contract Llm Developer specializes in legal language models, requiring legal expertise and an LLM degree, often working within legal tech or law-related industries. In contrast, a Contract Software Engineer focuses on software development skills and technical certifications, working across various tech sectors. While both roles involve AI and contract work, their core skills and industry applications differ significantly.

What are the most commonly searched types of Llm Developer jobs in Virginia?

The most popular types of Llm Developer jobs in Virginia are:

What are popular job titles related to Contract Llm Developer jobs in Virginia?

For Contract Llm Developer jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Contract Llm Developer jobs in Virginia look for?

The top searched job categories for Contract Llm Developer jobs in Virginia are:

What cities in Virginia are hiring for Contract Llm Developer jobs?

Cities in Virginia with the most Contract Llm Developer job openings:

Contract Llm Developer jobs near you

GENAI DEVELOPER

BTree Solutions, Inc.

Mclean, VA • On-site

Contractor

Re-posted yesterday

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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