Apply on Employer Site

Leidos · 7 hours ago

Automated Test Engineer 4

Gaithersburg, MD

Full-time

Onsite

Senior Level, Lead/Staff

$108K/yr - $195K/yr

8+ years exp

Leidos is a company redefining possibilities through innovation and collaboration. They are seeking an Automated Test Engineer to support the verification, validation, and qualification of advanced systems within the National Airspace System, focusing on automated testing methodologies and AI/ML techniques.

ComputerGovernmentInformation ServicesInformation TechnologyNational SecuritySoftware

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Responsible for DevOps-related activities both individually and as a member of an Agile team. Design, develop, and maintain automated test suites and frameworks using Squish, Selenium, and CI (e.g. Jenkins, Gitlab) to ensure the quality and reliability of software applications

Develop System of Systems (SoS) Test Architecture to ensure Large Scale Effectivity

Implement AI tools to enhance test automation

Troubleshoot and debug automated tests to identify root causes of failures and ensure test reliability

Work closely and collaborate with development teams to identify and verify testable requirements

Implement automated testing solutions and ensure that the software is testable and meets the requirement verification needs of the product

Write and execute automated test scripts using various testing tools and frameworks

Maintain clear and concise documentation

Track issues

Manage VMs & dev containers

Use CI/CD tools

Maintain test artifacts such as Verification Requirements Test Matrix

Participate in daily stand-ups, Sprint Planning, Release Planning, and other related team activities

Develop, implement, and maintain automated test frameworks to support verification and validation (V&V) of complex AI/ML systems within ATC environments

Design system-level and component-level test procedures, test cases, and data sets based on formal requirements and system specifications

Lead efforts to evaluate AI/ML model behavior, accuracy, and performance under operationally representative scenarios and datasets

Integrate automated test tools and continuous testing pipelines (e.g., CI/CD) to enhance system reliability and regression coverage

Conduct root cause analysis and defect resolution in coordination with software, systems, and AI engineering teams

Execute integration testing of distributed, safety-critical systems using containerized or virtualized environments

Develop performance metrics, traceability matrices, and test reports in accordance with FAA, NASA, or DoD documentation standards

Support test readiness reviews, system qualification events, and formal certification processes as required

Assure the functional integrity, reliability, and safety of mission-critical ATC expansion systems. Test results directly support system accreditation, operational readiness, and compliance with NAS modernization objectives

Perform highly complex test engineering functions requiring in-depth knowledge of AI/ML-based systems and automation frameworks. Develop innovative approaches to test design and data analysis to assess intelligent, adaptive system performance under dynamic conditions

Interface with multidisciplinary engineering teams, program management, subcontractors, and government representatives. Produce formal test documentation, analysis reports, and presentations in support of technical reviews and audits

Qualification

Automated TestingAI/ML TechniquesTest Framework DevelopmentCI/CD ToolsScripting LanguagesLinux/Unix EnvironmentsContainerizationChaos TestingAnalytical SkillsCommunication SkillsTechnical Documentation

Required

Due to US Government contract, must be a U.S. Citizen with the ability to obtain and maintain a Public Trust security clearance

Bachelor's degree in Computer Science, Systems Engineering, or related discipline, and at least 8 years of relevant experience (mid-to-senior level)

Demonstrated experience in automated testing, test framework development, and system-level verification of complex or safety-critical systems

Strong understanding of AI/ML test methodologies, data preprocessing, and performance evaluation metrics

Proficiency with scripting languages (Python, Bash) and automation tools (e.g., PyTest, Robot Framework, Jenkins, or similar)

Experience with Linux or Unix-based environments, containerization (Docker, Podman), and CI/CD pipelines

Knowledge of simulation frameworks, test harness development, and data-driven test execution

Excellent analytical, communication, and technical documentation skills

Experience with Chaos Testing principles

Proficient in automated test engineering principles, system verification, and AI system validation. Working knowledge of AI/ML model evaluation, data-driven testing, and automated test architectures is essential