Staff Engineer Test Automation
Shield AI is a U.S. defense-technology company developing mission-autonomy software and autonomous aircraft for military and allied operations.
Funding history
Investors
About Shield AI
Founded in 2015, Shield AI builds Hivemind autonomy software and V-BAT and X-BAT aircraft for operations in contested, GPS- and communications-denied environments. Its current site also presents Aechelon synthetic-reality simulation and Vision Systems detection and tracking products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own the strategy and architecture for automated testing, verification, and MLOps quality. You will build test and ML-validation frameworks, CI/CD workflows, observability, Python automation, simulation tools, and AI-assisted engineering workflows for distributed hardware and software systems.
Requirements
- 8+ years of relevant experience in software engineering, test infrastructure, developer tooling, MLOps, systems integration, or systems verification
- 5+ years building scalable automation frameworks or developer tooling in Python
- Experience designing test, CI/CD, or MLOps infrastructure across multiple engineering teams
- Experience validating machine-learning systems across their lifecycle
- Understanding of ML quality risks and model-performance baselines
- Experience testing GPU-accelerated infrastructure and workloads in Kubernetes
- Experience validating multi-tenant Kubernetes environments
- Experience qualifying integrated hardware and software systems
- System-design experience testing distributed systems, backend services, APIs, and integrated systems
- Experience developing integration and regression strategies
- Understanding of asynchronous and concurrent Python programming
- Experience with package and dependency management and reproducible environments
- Experience with observability, log collection, analytics, reporting, and root-cause analysis
- Experience working in Linux-based development environments
Responsibilities
- Own the technical strategy, architecture, and roadmap for automated testing, verification, and MLOps quality
- Design and maintain scalable test frameworks
- Lead functional, integration, regression, system, performance, reliability, and end-to-end testing
- Build automated ML validation pipelines
- Establish CI/CD and continuous-training workflows
- Develop scenario-based validation for autonomy models
- Create observability, analytics, and failure-triage capabilities
- Build Python automation for test execution and reporting
- Create test harnesses, simulators, stubs, mocks, and synthetic-data capabilities
- Define verification strategies with engineering stakeholders
- Develop and govern AI-assisted engineering workflows
Benefits
- Bonus
- Equity