Designs and integrates AI-enabled modernization solutions while establishing quality assurance frameworks for AI-generated code, skills, agents, and prototypes. Develops test plans, acceptance criteria, regression suites, automated testing, security scans, and quality gates. Collaborates with DevOps teams on reliable multi-agent workflows, validates prototypes for production readiness, and monitors accuracy, security, compliance, and data-sensitivity risks.
AI Quality Engineer
Full-Time | 100% Remote (U.S.)
Overview
The AI Quality Engineer supports a federal customer by helping design and implement AI-enabled solutions, developing and integrating AI capabilities, and ensuring that skills, agents, and AI-generated prototypes meet quality, security, and compliance standards as they move toward production. This work supports broader modernization goals, including automating and streamlining servicing operations, reducing manual processing, improving data quality, aligning with the customer’s modernization standards, and establishing a roadmap toward the eventual retirement of legacy platforms. Success requires a bachelor’s degree (or equivalent experience), demonstrated experience in software quality assurance and test engineering, hands-on experience validating AI-generated code and prototypes, familiarity with CI/CD pipelines and quality gates, strong analytical skills, and excellent written and verbal communication.
Key Functions
- Design and implement AI-enabled solutions for customer modernization use cases, developing and integrating AI capabilities into existing systems and workflows.
- Establish and enforce a quality assurance framework — test plans, acceptance criteria, and regression suites — for validating AI-generated code, skills, and agents before they are promoted through the innovation pipeline.
- Guide the development of reusable AI skills and agents for customer modernization tasks, with particular emphasis on automated testing, security scanning, data sensitivity, and scalability.
- Collaborate with DevOps engineers to create and orchestrate long-running, multi-agent workflows, ensuring reliability, observability, and recoverability in production environments.
- Support creation of the innovation pipeline that moves AI-generated (“vibe-coded”) prototypes from sandbox concepts into secure, enterprise-grade applications.
- Support Value Engineers’ efforts by reviewing and quality-checking prototype outputs for accuracy, reliability, and adherence to standards prior to pipeline promotion.
- Continuously monitor AI-assisted development outputs for accuracy, reliability, and compliance drift, feeding findings back to Value Engineers and AI Engineers to improve prompts, skills, and agents over time.
Minimum Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience.
- Demonstrated experience in software quality assurance, test engineering, or a related discipline, including test plan design and defect management.
- Hands-on experience testing or validating AI-generated code, prototypes, or “vibe-coded” solutions for accuracy and reliability.
- Experience with automated testing tools and frameworks (e.g., Selenium) across web and enterprise applications.
- Experience with one or more of the following: Salesforce, AWS (including Lambda and Redshift), Java, or PostgreSQL, or a comparable enterprise technology stack.
- Familiarity with CI/CD pipelines and quality gates within modern software delivery practices.
- Strong analytical skills, with the ability to identify security, data-sensitivity, and compliance risks in AI-assisted solutions.
- Excellent written and verbal communication skills, with the ability to work across product, engineering, data, and business SME teams.
- Must be a U.S. citizen and eligible to obtain and maintain a Public Trust clearance / favorable suitability determination.
Preferred Qualifications or Skills
- Direct experience supporting Federal clients.
- Experience with FedRAMP authorization processes.
- Mortgage, fintech, or other regulated industry experience (preferred, not required — willingness to learn quickly is essential).
- Familiarity with AI safety, governance, and compliance.
- Ability to use or teach tools such as ChatGPT, Claude, Gemini, Notion, Airtable, Zapier, LangChain, or similar.
- Experience in startups, consulting, internal strategy, learning & development (L&D), or innovation teams.
Position Details
- Employment type: Full-Time
- Location: 100% Remote (US-based)
- Hours: 8am–5pm ET
- Eligibility: Must be a U.S. citizen and suitable for, and eligible to obtain and maintain, a Public Trust clearance
Similar Jobs
Professional Services • Consulting
Own the company’s AI-powered quality and release infrastructure as its first dedicated hire. Build agent-run test harnesses, LLM graders, regression coverage, release gates, fresh-install and upgrade verification, and natural-language UAT. Manage CI health, artifact publication, deployment pipelines, credentials, certificates, and staging environments. Write production Python code, convert escaped bugs into regression tests, and provide trusted release-readiness evidence through dashboards, runbooks, retrospectives, and operating policies.
Top Skills:
AWSDockerGithub ActionsHelmKubernetesLlmsPlaywrightPythonSnowflake Native AppsTypescript
Artificial Intelligence • Cloud • Information Technology • Machine Learning • Natural Language Processing • Consulting
Leads enterprise quality engineering and test automation strategy across UI, API, integration, performance, and data layers. Architects Java-based automation frameworks, integrates quality gates into CI/CD pipelines, and drives AI/LLM adoption for test generation, debugging, self-healing, test data creation, and defect analysis. Establishes ETL and data validation practices, governs DevOps quality standards, mentors QA teams, and collaborates with Engineering, DevOps, Data Engineering, and Product stakeholders to improve quality maturity and delivery predictability.
Top Skills:
Ci/CdDevOpsDockerETLGithub CopilotGitlab CiJavaJenkinsKubernetesLlmsPlaywrightPostmanRestassuredSeleniumSwagger/Openapi
Artificial Intelligence • Food • Machine Learning • Software
Own the design and implementation of WISEcode’s automated quality engineering ecosystem. Build AI-augmented UI, API, integration, regression, database, performance, and reliability testing frameworks for ASP.NET and Blazor applications. Integrate testing into CI/CD, improve observability and release confidence, investigate failures and race conditions, validate AI/ML outputs, and establish scalable quality standards and metrics across engineering teams.
Top Skills:
Ai/MlAsp.NetBlazorC#Ci/CdCloud InfrastructureContainerizationCypressDuckdbLlmsMotherduckPlaywrightPostgresSelenium
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
