The company is looking to improve its systems-level thinking and hands-on capability across the entire product stack, from robotics hardware through edge and cloud infrastructure to user-facing mobile applications. This involves designing, validating, and continuously improving release processes, quality gates, and automation, while also tracing issues end-to-end and influencing engineering quality through data-driven insights.
Requirements
- 7+ years of experience in systems engineering, integration, automation, or release management, ideally in robotics, IoT, or complex digital platforms.
- Demonstrated ability to trace and debug issues across hardware, edge, cloud, and application layers, collaborating with specialists as needed.
- Proficiency in scripting/programming (Python, Bash, or similar) and familiarity with automation, CI/CD, and test frameworks.
- Strong analytical skills with experience in data processing and visualization (e.g., Python, Tableau, Grafana) to create actionable engineering insights.
- Experience making targeted improvements to automation, monitoring, or validation environments without being the primary owner of these systems.
- Experience with robotics, IoT, or hybrid hardware/software systems.
- Familiarity with cloud infrastructure, edge computing, and mobile application integration.
Responsibilities
- Trace and diagnose system-level issues spanning robotics hardware, edge devices, cloud services, and mobile applications, identifying integration gaps and collaborating with domain experts to resolve them.
- Partner with QA, SRE, and platform teams to design and refine release processes, establish actionable quality gates, and ensure robust validation across the product ecosystem.
- Make hands-on, targeted enhancements to automation scripts, test frameworks, and data pipelines as needed to support integration, validation, and observability efforts—leveraging but not replacing domain specialists.
- Analyze operational and test data, develop clear visualizations and dashboards, and communicate actionable insights that drive engineering and product decisions.
- Serve as a technical bridge, facilitating alignment and information flow between QA, DevOps, product, and AI/ML teams to ensure system-level quality and release readiness.
- Proactively identify opportunities to enhance automation, monitoring, and test coverage, and drive lessons learned into future release cycles.
Other
- Excellent communication and collaboration skills, with a proven ability to work effectively across multidisciplinary teams and technical domains.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent work experience).
- Background in data-driven quality assurance and release readiness assessment.
