{"schemaVersion":"jobsearcher.job.v1","id":"a0afd255d0449fa32ed23487","url":"https://jobsearcher.com/jobs/a0afd255d0449fa32ed23487","canonicalUrl":"https://jobsearcher.com/jobs/a0afd255d0449fa32ed23487","title":"Artificial Intelligence Engineer","description":"work sponsorship is available for this roleMust Have Qualifications: Must have 5+ years of experience and a strong AI development background. Must have hands on experience building agentic workflows, automating testing using AI, and working with tools such as GitHub, Copilot, and Claude.The candidate must have experience with the following:Testing & Automation: Playwright, Cypress, Karate, REST assuredProgramming: Java (APIs), JavaScript, TypeScriptAgentic AI skills: Agentic AI concepts, Prompt engineering, Creating markdown files, Building AI workflows, Developing AI agents, Integrating agents within GitHub Copilot LLMs: Azure OpenAI 4.6, Claude Sonnet 4.6Overview: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.Coverage standards, templates, and governance Define and publish coverage standards (what “good” looks like) including:Minimum coverage expectations by service/componentTest type mix (unit vs API vs UI vs contract vs integration)Risk-based prioritization and traceability to requirementsProvide templates usable across teams:Test plan templatesTest case/spec templates (Gherkin-style or equivalent)Definition of Ready / Definition of Done quality checklistsCreate a scalable tagging/metadata strategy (e.g., feature, service, risk, priority, data sensitivity) to support reporting and quality gates.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 narrativesFailure 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).“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 casesData/privacy considerations and environment needsIntegrate 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.Ability to design agent workflows for:Test generation/augmentationRequirements review and completeness validationReport generation and summarizationGitHub 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, templatesAutomation 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 scenariosNegative/validation scenariosEdge/boundary scenariosData 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 completenessRequired test data and environment dependenciesNon-functional requirements (performance, security, observability) when applicableDeliverables / 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 churnBenefits: We offer a benefits package including medical, dental, vision, and 401(k).Compensation: $100.00 – $110.00 per hour. This is the targeted compensation range for this role per year. Please note that this range is provided as a guideline and the final offer will be based on several factors, including but not limited to, skillset and competencies, level of experience, education, certifications, and location.We are an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable federal, state, or local law.","company":"Zillion Technologies","rawCompany":"zillion technologies","city":"McLean","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-07-23T12:52:34.265Z","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":"Artificial Intelligence Engineer","description":"work sponsorship is available for this roleMust Have Qualifications: Must have 5+ years of experience and a strong AI development background. Must have hands on experience building agentic workflows, automating testing using AI, and working with tools such as GitHub, Copilot, and Claude.The candidate must have experience with the following:Testing & Automation: Playwright, Cypress, Karate, REST assuredProgramming: Java (APIs), JavaScript, TypeScriptAgentic AI skills: Agentic AI concepts, Prompt engineering, Creating markdown files, Building AI workflows, Developing AI agents, Integrating agents within GitHub Copilot LLMs: Azure OpenAI 4.6, Claude Sonnet 4.6Overview: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.Coverage standards, templates, and governance Define and publish coverage standards (what “good” looks like) including:Minimum coverage expectations by service/componentTest type mix (unit vs API vs UI vs contract vs integration)Risk-based prioritization and traceability to requirementsProvide templates usable across teams:Test plan templatesTest case/spec templates (Gherkin-style or equivalent)Definition of Ready / Definition of Done quality checklistsCreate a scalable tagging/metadata strategy (e.g., feature, service, risk, priority, data sensitivity) to support reporting and quality gates.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 narrativesFailure 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).“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 casesData/privacy considerations and environment needsIntegrate 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.Ability to design agent workflows for:Test generation/augmentationRequirements review and completeness validationReport generation and summarizationGitHub 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, templatesAutomation 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 scenariosNegative/validation scenariosEdge/boundary scenariosData 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 completenessRequired test data and environment dependenciesNon-functional requirements (performance, security, observability) when applicableDeliverables / 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 churnBenefits: We offer a benefits package including medical, dental, vision, and 401(k).Compensation: $100.00 – $110.00 per hour. This is the targeted compensation range for this role per year. Please note that this range is provided as a guideline and the final offer will be based on several factors, including but not limited to, skillset and competencies, level of experience, education, certifications, and location.We are an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable federal, state, or local law.","datePosted":"2026-07-23T12:52:34.265Z","dateModified":"2026-07-23T12:52:34.265Z","hiringOrganization":{"@type":"Organization","name":"Zillion Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"McLean","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"a0afd255d0449fa32ed23487"},"url":"https://jobsearcher.com/jobs/a0afd255d0449fa32ed23487"}}