HI
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.
PhoenixTeam | AI Quality Engineer | Page 2
• 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.
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.
