Lead AI Engineer role focused on agentic test automation using LLM-powered agents in a hybrid setup in Tysons, VA.

Build and operate tool-using, multi-step LLM-powered agents with guardrails
Design agent workflows for test generation and augmentation
Design agent workflows for requirements review and completeness validation
Design agent workflows for report generation and summarization
Use GitHub Copilot in day-to-day development
Implement CI/CD and automation using GitHub Actions (CI/CD pipelines, reusable workflows, composite actions)
Support quality gates and governance via PR checks, branch protections, CODEOWNERS, and templates
Automate processes via GitHub APIs and webhooks as needed
Develop API and integration automation with Karate including API testing, contract-like checks, data-driven testing, and mocks
Develop UI automation with Playwright including selectors strategy, parallelization, and trace/video artifacts
Aggregate and normalize outcomes across multiple microservices and multiple pipelines
Produce actionable automated reports including trend analysis, failure clustering, and service correlation

Hands-on experience building LLM-powered agents (tool-using, multi-step reasoning, guardrails)
Experience with prompting patterns, structured outputs using JSON schemas, evaluation, and techniques to reduce hallucinations
Ability to design agent workflows for:
- Test generation and augmentation
- Requirements review and completeness validation
- Report generation and summarization
GitHub Copilot proficiency
Deep experience with GitHub Actions (CI/CD pipelines, reusable workflows, composite actions)
Deep experience with GitHub platform capabilities including PR checks, branch protections, CODEOWNERS, and templates
Automation via GitHub APIs and webhooks as needed
Advanced experience with Karate: API testing, contract-like checks, data-driven testing, mocks
Advanced experience with Playwright: UI automation, selectors strategy, parallelization, trace/video artifacts
Strong understanding of test design and coverage including:
- Happy path scenarios
- Negative/validation scenarios
- Edge/boundary scenarios
- Data setup/teardown strategies and test isolation
Proven ability to aggregate and normalize results from multiple microservices and multiple pipelines
Experience producing actionable automated reports (trend analysis, failure clustering, service correlation)

Lead AI Engineer – Agentic Test Automation

Job Description