Pano AI seeks a Staff Design Quality Engineer to act as the independent quality and systems-risk steward across hardware, firmware, software, and AI subsystems. The role requires end-to-end systems thinking and collaboration with various teams to identify and mitigate system-level risks. The ideal candidate will have 8+ years of experience in design quality, reliability engineering, systems engineering, or similar roles.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
The Role
Pano is seeking a Staff Design Quality Engineer with end-to-end systems thinking to act as the independent quality and systems-risk steward across hardware, firmware, software, and AI subsystems. You will partner deeply with Hardware, Software, AI and Operations teams to identify and mitigate system-level risks, define verification and validation strategies, and ensure our camera systems and analytics are designed to behave safely and reliably in the field. This role is both strategic (setting system-level risk posture and release criteria) and tactical (influencing good requirements and design, defining test methods, and closing evidence to support product releases and field improvements).
What you’ll do
- Serve as the Design Quality / Systems Quality representative embedded in one or more product teams — influence requirements, architecture, and release criteria from concept to production and sustaining.
- Lead and maintain system-level risk artifacts (e.g. system FMEAs/DFMEAs) and ensure traceability between risks, requirements, tests and mitigations.
- Define and own verification & validation strategy at the system-level: coordinate test plans, field trials, test method validation, statistical acceptance criteria and objective evidence for release.
- Drive risk-based decision making — prioritize mitigations given ambiguous tradeoffs and document rationale for release decisions and residual risk.
- Select and drive execution of reliability and stress tests that emulate real-world field conditions (e.g. power/thermal cycling, packet-loss/high-latency networks, exposure, OTA update failure modes).
- Collaborate with AI and product analytics to define observability & telemetry needed for model performance monitoring in the field and tie those signals back into verification and risk mitigation strategies.
- Mentor engineers and product teams on structured problem-solving (5-Whys, DMAIC, etc.) and quality best practices that scale across fast evolving hardware/AI products.
Looking to advance your Development & Programming career with relocation support? Explore Development & Programming Jobs with Relocation Packages that include comprehensive packages to help you move and settle in your new role.
What you’ll bring
- BS in Engineering (Mechanical, Electrical, Computer, Systems or related) or equivalent experience
- 8+ years’ experience in design quality, reliability engineering, systems engineering, or similar roles for products that combine hardware, firmware and software (embedded + cloud + AI).
- Proven experience owning system-level risk artifacts and applying risk-based decision making.
- Hands-on experience planning and executing verification & validation strategies, including test method selection/development and use of statistical techniques for acceptance criteria.
- Deep product empathy and demonstrable experience driving tradeoffs to improve field outcomes or customer experience.
- Excellent written and verbal communication skills — able to present technical findings and risk decisions to both engineers and executive stakeholders.
Discover our full range of relocation jobs with comprehensive support packages to help you relocate and settle in your new location.
Preferred
- Prior experience with camera systems, imaging pipelines, sensor fusion, or edge AI deployments.
- Experience with OTA update strategies, installed base telemetry, and telemetry-driven iteration of design and AI models.
- Experience with statistical tools (Minitab, Python data stack) and reliability models (Weibull, MTBF/MTTF analysis).
- Experience mentoring team members and scaling quality processes in a growing company.
Final compensation for full-time employees is determined by a variety of factors, including job-related qualifications, education, experience, skills, knowledge, and geographic location. In addition to base salary, full-time roles are eligible for stock options. Our benefits package also includes comprehensive medical, dental, and vision coverage, a matching 401(k) plan, and flexible paid time off. RELOCATION ASSISTANCE PROVIDED
Appl
Similar Jobs
Explore other opportunities that match your interests
Senior Machine Learning Engineer - Signal Processing
neurosonic
rmg digital