Lead AI Engineer - Agentic Test Automation

About the role

Job Summary

Fully onsite McLean, VA

location: Tysons, Virginia

job type: Contract

salary: $65 - 90 per hour

work hours: 9am to 5pm

education: Bachelors

Responsibilities

) Agentic test automation foundation (reusable patterns + reference implementations) o Minimum coverage expectations by service/component o Test plan templates 3) GenAI-assisted reporting and quality insights across microservices o Test execution results (Karate/Playwright + CI runs) o Release readiness narratives 4) "Quality gates" via agents o Required fields present (acceptance criteria, testable outcomes, data needs, dependencies)

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.

Coverage standards, templates, and governance

Define and publish coverage standards (what "good" looks like) including:

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 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.

Build automated reporting that aggregates test + service data across multiple microservices, such as:

Service health signals (logs/metrics/traces if available)

Defect signals (issue tracker metadata if available)

Generate GenAI-driven summaries:

Failure clustering and trend analysis

"What changed?" insights (commit/PR correlation)

Produce outputs consumable by engineering leadership and teams (dashboards, markdown summaries in PRs, artifacts in CI).

Build automated review agents that evaluate user stories/requirements for minimum required clarity and data before development/testing starts:

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.

Qualifications

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.

Ability To Design Agent Workflows For

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

Skills

API testing,APIs,API,Test automation,data-driven testing,data management,data aggregation,Gherkin,GitHub Copilot,GitHub Actions,GitHub,JSON,LLM-powered,microservices,UI automation,parallelization,Playwright,Test case,test data,Test execution,webhooks,organization,leadership,acceptance criteria,architecture,Automation,automated,composite,dashboards,automated reporting,Failure analysis,Underwriting,governance,tagging,maintenance,metrics,publish,Risk,security,Non-functional requirements,test design,Test plan,testing,trend analysis,triage,user stories,workflows

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.