AI Quality & Test Engineer

• US Citizenship and the ability to obtain and maintain a Public Trust clearance are required
• Bachelor's Degree is required
• Minimum of 8 years' position related experience is required
• AWS Certified AI Practitioner or Developer (Associate) certification preferred for hire; the AWS and Anthropic Claude certifications listed under Required Certifications must be earned within 12 months of hire
• Remote position with occasional travel to client sites and STS events
• Candidates living in the DC Metro region (within driving distance for quarterly in-person team events) are strongly preferred; STS is a HUBZone company, so residence in a HUBZone is favored for remote candidates

The AI Quality & Test Engineer owns the second human bookend of the STS SDLC: proving that what the team built does what the requirements say, works end to end for real users, and behaves acceptably as an AI system. You design the test strategy from the requirements trio, build and run end-to-end and user-acceptance testing, and define how AI outputs are evaluated so that quality is measured rather than assumed. Success looks like test gates the team trusts, defects found before users do, and clear evidence at every release that the solution meets its acceptance criteria. You bring the same discipline to engagements that run on AWS-native AI services or other client toolchains.

• Define the test strategy for each AI application project from the requirements trio, including unit, integration, end-to-end, user-acceptance, security, and AI-behavior testing, and the coverage and gate thresholds the project will use.
• Design, build, and execute end-to-end and user-acceptance tests that exercise complete use cases as real users would, across DEV, TST, STG, and PRD.
• Build evaluation harnesses for AI behavior, including golden datasets, rubric-based and model-assisted grading, regression suites for prompts and retrieval, and guardrail and safety checks.
• Operate as the tester in the team's AI development workflow, using and improving the shared testing agents and skills, and ensuring tests derived from use cases exist before application code is written.
• Automate tests in the CI/CD pipeline in partnership with the platform engineer, and own the quality gates that govern promotion between environments.
• Validate acceptance criteria with the business analyst and real users, facilitate user-acceptance testing sessions, and capture results as release evidence.
• Triage, reproduce, and track defects in Jira, drive them to resolution with engineers, and analyze defect trends to improve upstream requirements and development practices.
• Test on AWS-native AI stacks, including Amazon Bedrock models, agents, and knowledge bases, when a client requires them in place of STS's standard toolchain.
• Assess performance, cost, and resilience of AI features under realistic load and failure conditions, and report findings with recommendations.
• Contribute test standards, templates, and tooling back to the STS SDLC, and coach the team on test-driven development and AI evaluation practices.

Required

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field, or equivalent professional experience in addition to the minimum below
• Minimum of 8 years of software quality engineering or test automation experience, including at least 2 years testing applications built on large language models or other AI/ML components
• Demonstrated experience building automated end-to-end test suites integrated into CI/CD pipelines and defining quality gates for a delivery team
• Experience leading user-acceptance testing with business or mission users, ideally in a federal or regulated environment
• Strong test automation skills in Python or TypeScript using frameworks such as Playwright, pytest, or Jest, plus API testing tools
• Practical knowledge of LLM evaluation techniques, including golden datasets, rubric and model-graded evaluation, retrieval quality metrics, and prompt and model regression testing
• Working knowledge of Amazon Bedrock and AWS application services sufficient to test and troubleshoot deployed AI features
• Fluency with GitHub, Jira, and CI/CD pipelines, and with reading use cases and specifications to derive tests
• Familiarity with security testing basics and federal compliance expectations for test evidence
• Skeptical in the best sense; assumes nothing works until it is demonstrated, including AI output that reads well
• Collaborative and constructive, treating defects as information for the team rather than blame
• Self-directed and comfortable owning outcomes on a small, senior team where everyone contributes across the lifecycle
• Curious and current on AI tooling; treats AI assistants as part of the team and holds their output to the same standard as human work
• Clear, candid communicator with federal clients and teammates; writes well and documents as a habit
• Bias toward fast delivery and early user feedback over conservative gating; learns from failure quickly

Required Certifications (to be earned within 12 months of hire)

• AWS Certified AI Practitioner or AWS Certified Developer – Associate
• Claude Certified Developer – Foundations (CCDV-F) or Claude Certified Associate – Foundations (CCAO-F)

Preferred Certifications

• ISTQB Certified Tester Foundation Level (CTFL) and ISTQB Certified Tester AI Testing (CT-AI)
• AWS Certified Solutions Architect – Associate
• CompTIA Security+
• Certified ScrumMaster (CSM) or Professional Scrum Master (PSM I)