Software Technologist I – Automation Framework

Job Title

Software Technologist I – Automation Framework

Job Description

As a Software Technologist I, you will lead software development activities across the software development lifecycle by analyzing requirements, influencing software design, developing scalable automation solutions and delivering high-quality engineering products.You will design, develop and maintain scalable automation frameworks, reusable libraries and engineering tools supporting embedded software verification.

Your role:

- Develop robust object-oriented software solutions using C#, .NET, Python, C++, or similar technologies while following software engineering best practices.

- Integrate automation frameworks, software components and third-party libraries into Azure DevOps (ADO), GitHub, Git, CI/CD pipelines and DevOps workflows to deliver reliable and maintainable automation solutions.

- Drive Behavior-Driven Development (BDD) by developing reusable Gherkin scenarios, automation components and framework capabilities.

- Develop software for logging, analytics, performance monitoring and engineering productivity dashboards to improve framework reliability and operational insights.

- Support Hardware-in-the-Loop (HIL) integration, simulators, engineering test infrastructure and framework interoperability.

- Conduct comprehensive code reviews and participate in design reviews to ensure adherence to coding standards, identify potential issues and promote software engineering best practices, maintainability and continuous improvement.

- Lead complex software defect investigations through debugging, log analysis, root cause analysis and performance optimization while collaborating with cross-functional engineering teams.

- Create and maintain technical documentation, including software architecture diagrams, API specifications, framework design documentation and user guides to facilitate knowledge sharing and long-term maintainability.

- Evaluate, adopt and promote AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) and AI/ML techniques for automation, intelligent test generation, anomaly detection and engineering productivity improvements.

- Continuously evaluate emerging software technologies, automation methodologies and engineering best practices to drive innovation and improve engineering productivity.