{"schemaVersion":"jobsearcher.job.v1","id":"d4ba7a89faca9c7c70681ed8","url":"https://jobsearcher.com/jobs/d4ba7a89faca9c7c70681ed8","canonicalUrl":"https://jobsearcher.com/jobs/d4ba7a89faca9c7c70681ed8","title":"AI Developer","description":"McLean, Virginia 22043 Posted September 15th, 2026\nJob Type: Contract\nJob Category: IT\nJob Description\n\nRole - AI Developer\nLocation – Mclean, VA\nContract\n\nJob Description:\n\nRequired Technical Skills :\n\nGenAI / LLM + agentic development\n\n· Hands-on experience building LLM-powered agents (tool-using, multi-step reasoning, guardrails).\n\n· Experience with prompting patterns, structured outputs (JSON schemas), evaluation, and reducing hallucinations.\n\n· Ability to design agent workflows for:\n\no Test generation/augmentation\n\no Requirements review and completeness validation\n\no Report generation and summarization\n\nGitHub platform + GHCP (Copilot) for engineering workflows\n\n· Strong proficiency with GitHub Copilot in day-to-day development.\n\n· Deep experience with GitHub platform capabilities:\n\nTest automation engineering (framework expertise)\n\n· Advanced experience designing and implementing automation with:\n\no Karate (API testing, contract-like checks, data-driven testing, mocks)\n\no Playwright (UI automation, selectors strategy, parallelization, trace/video artifacts)\n\n1) Agentic test automation foundation (reusable patterns + reference implementations)\n\n· Design and implement agentic testing patterns that can be adopted by multiple Underwriting teams (and later other domains).\n\n· Create reference implementations (sample repos / templates) demonstrating:\n\no Test generation assistance (from requirements, APIs, contracts, schemas)\n\no Test maintenance assistance (auto-updating selectors/contracts, flaky test triage)\n\no Failure analysis assistance (root cause suggestions, log correlation, defect drafting)\n\n· Establish a standard architecture for test code organization, tagging, data management, and execution across UI + API + service layers.\n\n2) Coverage standards, templates, and governance\n\n· Define and publish coverage standards (what “good” looks like) including:\n\no Minimum coverage expectations by service/component\n\no Test type mix (unit vs API vs UI vs contract vs integration)\n\no Risk-based prioritization and traceability to requirements\n\n· Provide templates usable across teams:\n\no Test plan templates\n\no Test case/spec templates (Gherkin-style or equivalent)\n\no Definition of Ready / Definition of Done quality checklists\n\n· Create a scalable tagging/metadata strategy (e.g., feature, service, risk, priority, data sensitivity) to support reporting and quality gates.\n\n3) GenAI-assisted reporting and quality insights across microservices\n\n· Build automated reporting that aggregates test + service data across multiple microservices, such as:\n\no Test execution results (Karate/Playwright + CI runs)\n\no Service health signals (logs/metrics/traces if available)\n\no Defect signals (issue tracker metadata if available)\n\n· Generate GenAI-driven summaries:\n\no Release readiness narratives\n\no Failure clustering and trend analysis\n\no “What changed?” insights (commit/PR correlation)\n\n· Produce outputs consumable by engineering leadership and teams (dashboards, markdown summaries in PRs, artifacts in CI).\n\n4) “Quality gates” via agents\n\n· Build automated review agents that evaluate user stories/requirements for minimum required clarity and data before development/testing starts:\n\no Required fields present (acceptance criteria, testable outcomes, data needs, dependencies)\n\no Ambiguity detection and missing edge cases\n\no Data/privacy considerations and environment needs\n\n· Integrate gates into workflow (PR checks, issue templates, GitHub Actions) to reduce churn and rework.\n\nRequired Skills\nCloud Developer SQL Application Developer","company":"Realign","rawCompany":"realign","city":"McLean","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-09-16T10:34:50.832Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1253.00","title":"Software Quality Assurance Analysts and Testers","slug":"software-quality-assurance-analysts-and-testers"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AI Developer","description":"McLean, Virginia 22043 Posted September 15th, 2026\nJob Type: Contract\nJob Category: IT\nJob Description\n\nRole - AI Developer\nLocation – Mclean, VA\nContract\n\nJob Description:\n\nRequired Technical Skills :\n\nGenAI / LLM + agentic development\n\n· Hands-on experience building LLM-powered agents (tool-using, multi-step reasoning, guardrails).\n\n· Experience with prompting patterns, structured outputs (JSON schemas), evaluation, and reducing hallucinations.\n\n· Ability to design agent workflows for:\n\no Test generation/augmentation\n\no Requirements review and completeness validation\n\no Report generation and summarization\n\nGitHub platform + GHCP (Copilot) for engineering workflows\n\n· Strong proficiency with GitHub Copilot in day-to-day development.\n\n· Deep experience with GitHub platform capabilities:\n\nTest automation engineering (framework expertise)\n\n· Advanced experience designing and implementing automation with:\n\no Karate (API testing, contract-like checks, data-driven testing, mocks)\n\no Playwright (UI automation, selectors strategy, parallelization, trace/video artifacts)\n\n1) Agentic test automation foundation (reusable patterns + reference implementations)\n\n· Design and implement agentic testing patterns that can be adopted by multiple Underwriting teams (and later other domains).\n\n· Create reference implementations (sample repos / templates) demonstrating:\n\no Test generation assistance (from requirements, APIs, contracts, schemas)\n\no Test maintenance assistance (auto-updating selectors/contracts, flaky test triage)\n\no Failure analysis assistance (root cause suggestions, log correlation, defect drafting)\n\n· Establish a standard architecture for test code organization, tagging, data management, and execution across UI + API + service layers.\n\n2) Coverage standards, templates, and governance\n\n· Define and publish coverage standards (what “good” looks like) including:\n\no Minimum coverage expectations by service/component\n\no Test type mix (unit vs API vs UI vs contract vs integration)\n\no Risk-based prioritization and traceability to requirements\n\n· Provide templates usable across teams:\n\no Test plan templates\n\no Test case/spec templates (Gherkin-style or equivalent)\n\no Definition of Ready / Definition of Done quality checklists\n\n· Create a scalable tagging/metadata strategy (e.g., feature, service, risk, priority, data sensitivity) to support reporting and quality gates.\n\n3) GenAI-assisted reporting and quality insights across microservices\n\n· Build automated reporting that aggregates test + service data across multiple microservices, such as:\n\no Test execution results (Karate/Playwright + CI runs)\n\no Service health signals (logs/metrics/traces if available)\n\no Defect signals (issue tracker metadata if available)\n\n· Generate GenAI-driven summaries:\n\no Release readiness narratives\n\no Failure clustering and trend analysis\n\no “What changed?” insights (commit/PR correlation)\n\n· Produce outputs consumable by engineering leadership and teams (dashboards, markdown summaries in PRs, artifacts in CI).\n\n4) “Quality gates” via agents\n\n· Build automated review agents that evaluate user stories/requirements for minimum required clarity and data before development/testing starts:\n\no Required fields present (acceptance criteria, testable outcomes, data needs, dependencies)\n\no Ambiguity detection and missing edge cases\n\no Data/privacy considerations and environment needs\n\n· Integrate gates into workflow (PR checks, issue templates, GitHub Actions) to reduce churn and rework.\n\nRequired Skills\nCloud Developer SQL Application Developer","datePosted":"2026-09-16T10:34:50.832Z","dateModified":"2026-09-16T10:34:50.832Z","hiringOrganization":{"@type":"Organization","name":"Realign","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"McLean","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d4ba7a89faca9c7c70681ed8"},"url":"https://jobsearcher.com/jobs/d4ba7a89faca9c7c70681ed8"}}