Location:

McLean, VA\n

Duration:

5-6 months\n

Description:

\nAgentic test automation foundation (reusable patterns + reference implementations)\nDesign and implement agentic testing patterns that can be adopted by multiple Underwriting teams (and later other domains).\nCreate reference implementations (sample repos / templates) demonstrating:\nTest generation assistance (from requirements, APIs, contracts, schemas)\nTest maintenance assistance (auto-updating selectors/contracts, flaky test triage)\nFailure analysis assistance (root cause suggestions, log correlation, defect drafting)\nEstablish a standard architecture for test code organization, tagging, data management, and execution across

UI + API

+ service layers.\nCoverage standards, templates, and governance\nDefine and publish coverage standards (what \"good\" looks like) including:\nMinimum coverage expectations by service/component\nTest type mix (unit vs API vs UI vs contract vs integration)\nRisk-based prioritization and traceability to requirements\nProvide templates usable across teams:\nTest plan templates\nTest case/spec templates (Gherkin-style or equivalent)\nDefinition of Ready / Definition of Done quality checklists\nCreate a scalable tagging/metadata strategy (e.g., feature, service, risk, priority, data sensitivity) to support reporting and quality gates.\nGenAI-assisted reporting and quality insights across microservices\nBuild automated reporting that aggregates test + service data across multiple microservices, such as:\nTest execution results (Karate/Playwright + CI runs)\nService health signals (logs/metrics/traces if available)\nDefect signals (issue tracker metadata if available)\nGenerate GenAI-driven summaries:\nRelease readiness narratives\nFailure clustering and trend analysis\n\"What changed?\" insights (commit/PR correlation)\nProduce outputs consumable by engineering leadership and teams (dashboards, markdown summaries in PRs, artifacts in CI).\nQuality gates\" via agents\nBuild automated review agents that evaluate user stories/requirements for minimum required clarity and data before development/testing starts:\nRequired fields present (acceptance criteria, testable outcomes, data needs, dependencies)\nAmbiguity detection and missing edge cases\nData/privacy considerations and environment needs\nIntegrate gates into workflow (PR checks, issue templates, GitHub Actions) to reduce churn and rework.\nRequired Technical Skills (must-have)\nGen

AI / LLM

+ agentic development\nHands-on experience building LLM-powered agents (tool-using, multi-step reasoning, guardrails).\nExperience with prompting patterns, structured outputs (JSON schemas), evaluation, and reducing hallucinations.\nAbility to design agent workflows for:\nTest generation/augmentation\nRequirements review and completeness validation\nReport generation and summarization\nGitHub platform + GHCP (Copilot) for engineering workflows\nStrong proficiency with GitHub Copilot in day-to-day development.\nDeep experience with GitHub platform capabilities:\nGitHub Actions (CI/CD pipelines, reusable workflows, composite actions)\nPR checks, branch protections, CODEOWNERS, templates\nAutomation via GitHub APIs/webhooks (as needed)\nTest automation engineering (framework expertise)\nAdvanced experience designing and implementing automation with:\nKarate (API testing, contract-like checks, data-driven testing, mocks)\nPlaywright (UI automation, selectors strategy, parallelization, trace/video artifacts)\nStrong understanding of test design and coverage:\nHappy path scenarios\nNegative/validation scenarios\nEdge/boundary scenarios\nData setup/teardown strategies and test isolation\nCross-service reporting and data aggregation\nProven ability to aggregate and normalize results from multiple microservices and multiple pipelines.\nExperience producing actionable automated reports (trend analysis, failure clustering, service correlation).\nAutomated requirements review agents\nExperience implementing automated checks that validate:\nAcceptance criteria completeness\nRequired test data and environment dependencies\nNon-functional requirements (performance, security, observability) when applicable\nDeliverables / What success looks like (for the posting)\nA reusable agentic testing automation kit adopted by multiple teams.\nPublished coverage standards + templates and onboarding documentation.\nA working GenAI-assisted reporting pipeline aggregating results across microservices.\nAutomated quality gates integrated into GitHub workflows that measurably reduce story churn.\n

Call Notes:

Required Skills:

\nGenAI + agentic AI + Prompt Engineering\nGenerating Test Cases\nPlaywright\nkanban agile Environment\nJava and JavaScript\nCopilot and GitHub\nAPI based on Java\nUI Based Typescript\n

Call Notes:

Must Have Qualifications:

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