Responsibilities
- Contribute to impactful automation initiatives focused on endpoint visibility and management, delivering measurable improvements in customer operations.
- Exercise technical ownership by leading the design and implementation of end-to-end automation solutions and shaping reusable standards and libraries.
- Apply modern development practices using Git-based CI/CD pipelines and AI-powered coding tools to enhance development speed and code integrity.
- Expand proficiency in analytics query languages and automation techniques across varied endpoint environments.
- Evaluate automation and reporting needs from stakeholders and convert them into reliable, efficient technical implementations.
- Develop and sustain robust PowerShell and Bash scripts tailored for device management, data telemetry, and incident resolution on Windows and macOS systems.
- Connect automation workflows with analytics platforms via API integrations to retrieve endpoint data, initiate actions, and coordinate responses.
- Create and refine automated runbooks for key operations including software updates, compliance checks, and issue remediation.
- Link scripting outputs and API interactions with third-party systems such as REST services, webhooks, and service management platforms for seamless automation.
- Improve and restructure legacy automation code to increase modularity, reuse, and long-term maintainability.
- Produce clear, comprehensive documentation for scripts, integrations, and procedures to support client adoption and ongoing maintenance.
- Keep current with evolving platform features, operating system updates, automation technologies, and security protocols.
- Diagnose and resolve issues in automation workflows to ensure consistent performance and reliability.
- Engage in peer code reviews and help advance internal best practices for scripting and automation.
- Leverage AI-assisted development tools to speed up script creation, testing, and refactoring while maintaining code quality and security.
- Implement AI-enhanced validation methods to test automation logic, including edge cases and recovery procedures.
- Adhere to secure coding standards when using AI tools, including human oversight, protection of sensitive information, and tracking of code origins.
