Integration & Test Automation Engineer (AI Platform)

Responsibilities

We are seeking an Integration & Test Automation Engineer to strengthen our multi-stage DevSecOps workflows and ensure our platform meets reliability, security, and quality standards across development, staging, and production. In this role, you will create and maintain high-coverage automated test suites, validate system integrations (including AI components), and work hands-on with CI/CD pipelines and cloud-based test environments. You’ll collaborate cross-functionally with software, system engineering & quality, and platform release teams. You’ll also engage with customer-facing test activities and have an opportunity to influence how we validate state-of-the-art AI-enabled engineering solutions. Key Responsibilities: Develop, maintain, and enhance automated unit, integration, regression, and end-to-end test suites using tools like Pytest, JUnit, and Selenium/Cypress. Validate integrations between APIs, microservices, model-based systems engineering (MBSE) layers, and AI pipeline components. Work closely with system engineers to plan, automate, and execute comprehensive model-based systems engineering (MBSE) test scenarios. Integrate automated test executions into GitLab CI/CD pipelines, ensuring robust stage gating (local, dev, staging, prod). Design and implement thorough test plans, including system, performance, security, and UAT testing; track coverage/metrics against exit criteria. Build, deploy, and test environments using Kubernetes, Docker, and infrastructure automation with Terraform and/or AWS CloudFormation. Write scripts/tools in Python, Bash, PowerShell, and TypeScript to support test automation, data setup, CI/CD hooks, and system validation; apply Regex for data parsing/validation as appropriate. Leverage Prometheus/Grafana to validate system metrics as part of test runs and post-deployment checks. Quickly analyze test failures, assist development teams in debugging, and support defect tracking and resolution throughout the delivery cycle. Engage with Developers, Systems Engineers, and Platform/Quality teams from requirements discovery through deployment and handover

Qualifications

Required: Bachelor’s (8-10 years) or Master’s degree (6-8 years) or PhD (3-5 years) in Computer Science, Engineering, or a closely related field. 2–5 years in software/system testing or QA roles, preferably in complex, CI/CD-driven environments. Proficiency in developing automated test scripts using modern frameworks (e.g., Pytest for Python, JUnit, Selenium/Cypress for web UI, etc.). Experience testing REST APIs, microservices, and containerized (Docker/Kubernetes) applications. Hands-on with GitLab, automated pipelines, code branching/merging, and artifact promotion strategies. Direct experience running tests or deploying environments on AWS and/or Azure. Comfortable working jointly with Dev, Quality, and Ops teams, and engaging in customer-driven test/acceptance cycles. Analytical and proactive mindset in defect isolation, root-causing, and proposing corrective actions. Ability to obtain/maintain Secret Clearance. Preferred Skills: Familiarity with load testing tools, DAST/IAST, or other runtime security scanning. Experience using Prometheus/Grafana for test validation and system observability. Exposure to evaluating AI model outputs or integrating model quality into test plans (MLflow or similar). Familiarity with digital engineering concepts, SysML, or model-based system workflows. Experience preparing test reports, validation evidence, and supporting formal acceptance reviews. Technology and Tools: Languages: Python, Rust, Java, JavaScript (React/Redux), TypeScript, Bash, PowerShell, RegEx Cloud/Infrastructure: AWS, Azure, Kubernetes, Docker, Terraform, CloudFormation DevSecOps: GitLab, Maven, Semgrep, yGuard, OWASP, DAST/IAST Testing/Observability: pytest, JUnit, Jacoco, OTel, Grafana Stack, MLflow AI/ML: GPT models, Claude models, Embedding Models, LangChain, LlamaIndex, MCP MBSE/Domain: Cameo Systems Modeler, Teamwork Cloud, SysML v1 and v2 Equal Pay Act This is the projected compensation range for this position. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, Arcfield invests in its employees beyond just compensation. Arcfield ’s benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, Short Term and Long-Term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections. Min: $101,156.77 Max: $199,035.68 EEO Statement We are an equal opportunity employer and federal government contractor. We do not discriminate against any employee or applicant for employment as protected by law.