Firmware Program Manager

Required Qualifications & Skills

• Education & Experience: Bachelor's degree in Computer Science, Electrical/Computer Engineering, or a related technical field. 5+ years of experience in program management or project leadership within a technology environment (preferably involving software/firmware development or testing). Demonstrated success managing complex projects or programs with cross-functional teams.• Technical Domain Knowledge: Solid understanding of the software/firmware development life cycle and software testing processes. Familiarity with embedded systems or firmware for hardware devices is highly beneficial for context in this role.• Project Management Skills: Proven expertise in both Agile and Waterfall project management methodologies. Able to plan sprints or project phases, run Scrum ceremonies or schedule reviews, and adapt process as needed. Proficiency with project management and collaboration tools – especially JIRA for issue/task tracking and Confluence or similar for documentation – is required.• Data Analytics & Reporting: Strong data analysis skills and a metrics-driven approach to management. Able to define meaningful metrics for program success, and comfortable analyzing large data sets (e.g. test results, defect trends) to derive insights. Experience creating reports or dashboards using Power BI (or similar BI/analytics tools) to communicate status and support decision-making is required.• Programming/Scripting: Hands-on ability with Python programming for automation or data processing tasks. You should be capable of writing or understanding scripts to automate test processes or to manipulate and analyze test data. (Direct firmware coding experience is not required, but the ability to engage with engineers on technical details and contribute to tooling via scripts is important.)• AI/ML Familiarity: Knowledge of basic machine learning concepts and AI tools in a data analytics context. The ideal candidate can work with data scientists or engineers to apply AI/ML techniques for predicting failures, optimizing test coverage, or other process improvements. Experience leveraging AI/ML for real-world engineering or quality analytics is a strong plus.• Soft Skills: Excellent communication and stakeholder management skills are a must. Able to clearly convey complex information (e.g. technical issues, data insights, program status) to both technical and non-technical audiences. Strong organizational and leadership capabilities, including the ability to lead through influence and keep teams focused on shared goals. Demonstrated problem-solving aptitude and a proactive, ownership-driven attitude toward overcoming challenges.• Teamwork: A track record of effective collaboration in cross-functional and multi-cultural/global teams. Ability to work across time zones and adapt to work with team members in different geographic locations. High degree of flexibility and cultural awareness in coordinating a global test effort.