Help us tackle the growing wildfire crisis with the latest advancements in AI and IoT
Who we are
Every minute matters in fire response. As climate change amplifies the intensity of wildfires-with longer fire seasons, dryer fuels, and faster winds-new ignitions spread faster and put more communities at risk. Today, most wildfires are detected by bystanders and reported via 911, meaning it can take hours to detect a fire, verify its exact location and size, and dispatch first responders. Fire authorities need a faster way to detect, confirm, and pinpoint fires so that they can quickly respond-preventing small flare-ups from becoming devastating infernos.
About Pano: We are a 150+ person growth-stage hybrid-remote start-up, headquartered in San Francisco. We are the leader in early wildfire detection and intelligence, helping fire professionals respond to fires faster and more safely-with the right equipment, timely information, and enhanced coordination-so that they can stop a new ignition before it grows. Pano AI combines advanced hardware, software, and artificial intelligence into an easy-to-use, web-based platform. Leveraging a network of ultra-high-definition, 360-degree cameras atop high vantage points, as well as satellite and other data feeds, Pano AI produces a real-time picture of threats in a geographic region and delivers immediate, actionable intelligence.
Pano AI is on TIMEs list of the 100 Most Influential Companies of 2025! MIT Technology Review listed Pano as one of the top 15 climate tech companies to watch in 2024, and Fast Company named Pano AI one of the Top 10 most innovative companies in AI of 2023. We've also been featured in the Wall Street Journal, Bloomberg, and CNBC News. Pano AI's dozens of government and enterprise customers span 16 states in the U.S., five states in Australia, and BC, Canada, and we are currently monitoring over 30 million acres of land. Pano AI has raised $89M in venture capital funding from Giant Ventures, Liberty Mutual Ventures, Tokio Marine Future Fund, Congruent Ventures, Initialized Capital, Salesforce Ventures, and T-Mobile Ventures. Learn more at https://www.pano.ai/.
The Role
Pano is seeking a Senior/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).
Responsibilities
Serve as the Design Quality / Systems Quality representative embedded in one or more product teams - influence requirements, architecture, and release criteria from concept through 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.
Requirements
BS in Engineering (Mechanical, Electrical, Computer, Systems or related) or equivalent experience
10+ 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.
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.