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Lead Quality Automation Engineer – AI Platform

Job in Washington, District of Columbia, 20022, USA
Listing for: InSite
Full Time position
Listed on 2026-09-20
Job specializations:
  • Software Development
    AI QA / Validation Engineer, Software Testing
Salary/Wage Range or Industry Benchmark: 120000 - 170000 USD Yearly USD 120000.00 170000.00 YEAR
Job Description & How to Apply Below

We are seeking a Senior Test Automation Engineer & Quality Engineering Lead to establish and scale quality engineering for a modern AI platform and AI-enabled applications.

This is a hands-on, player-coach role responsible for defining the automation strategy, building reusable frameworks and critical test suites, integrating quality into CI/CD, and helping engineering teams increasingly own product quality.

The role spans web and mobile applications, APIs and backend services, data and integrations, and AI/agent behavior.

Key Responsibilities
  • Define an automation-first strategy across UI, APIs, services, integrations, data, and AI workflows.
  • Build reusable automation frameworks and high-value regression suites, with API/service-level testing as the foundation
    .
  • Automate critical web, mobile, and end-to-end journeys, including authentication, authorization, multi-tenant behavior, asynchronous interactions, and failure scenarios.
  • Integrate automated tests and quality gates into CI/CD pipelines.
  • Establish test execution monitoring, failure triage, reporting, and flaky-test management.
  • Automate critical performance, latency, resilience, concurrency, and dependency-failure scenarios.
AI, Agent & Data Quality
  • Establish repeatable evaluation and regression testing for Generative AI and agentic applications.
  • Validate appropriate tool and data usage, workflow and authorization boundaries, human-approval controls, and handling of missing or conflicting information.
  • Validate groundedness, factual accuracy, relevance, evidence quality, hallucination risk, instruction adherence, latency, and reliability.
  • Test retrieval, tool-calling, multi-step agent workflows, and AI application failure scenarios.
  • Automate data-quality validation covering freshness, integrity, completeness, transformation, traceability, and tenant isolation.
  • Establish representative synthetic and simulated datasets for deterministic regression and AI evaluation.
Engineering Leadership
  • Build the initial automation architecture and highest-value test suites.
  • Lead automation design, code quality, and engineering standards.
  • Partner with software, platform, data, AI, and Dev Ops engineers to embed testability early.
  • Participate in architecture and design reviews and mentor engineers contributing to shared automation frameworks.
  • Promote the right mix of unit, API, integration, end-to-end, performance, exploratory, and AI evaluation testing while driving distributed quality ownership.
Experience & Technology Skills

Strong candidates will have:

  • Senior-level test automation or quality engineering experience, including designing automation frameworks from the ground up.
  • Strong Python skills for API, service, data, and AI test automation.
  • Strong web, API/service, integration, and end-to-end automation experience.
  • Experience with automated testing of iOS and Android applications; cross-platform mobile automation is desirable.
  • Strong experience testing REST APIs
    , asynchronous services, authentication, authorization, and multi-tenant systems.
  • Strong SQL and data-validation skills across relational, operational, time-series, and document-oriented data.
  • Hands-on experience testing applications and services deployed on AWS
    ; AWS application, data, container, and observability services are strongly preferred.
  • Experience testing applications built with OpenAI models/APIs or comparable production LLM platforms;
    OpenAI experience preferred.
  • Hands-on experience with Generative AI and agentic systems
    , including retrieval, grounding, tool-calling, multi-step workflows, behavioral regression, hallucination/evidence validation, and AI observability.
  • Experience integrating automated testing into Git-based CI/CD workflows;
    Bitbucket and Bitbucket Pipelines experience preferred.
  • Experience…
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