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HomeCompaniesPano AiSenior/Staff Design Quality Engineer

Senior/Staff Design Quality Engineer

Pano Ai · San Francisco, California · Hybrid · Active · Ashby

Job facts

FieldValue
CompanyPano Ai
TitleSenior/Staff Design Quality Engineer
Normalized title-
Department / teamOperations / Operations
LocationSan Francisco, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary-
Statusactive
ATS providerAshby
Posted / first seen / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

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PageWhat it containsOpen
Company jobsActive postings from Pano Ai.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Ashby.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Operations.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyPano Ai
Source42564cd3-4567-4ad3-b189-37b21b8c14ea
ATS providerAshby

Description

Help us tackle the growing wildfire crisis with the latest advancements in AI and IoT Who we are The problem: 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 175+ 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 has been recognized by Fast Company as one of the Top 10 Most Innovative AI Companies in 2023, and as one of the Top 50 Most Innovative Companies of 2026 — ranking #1 in the Sustainability category. The company was also named to TIME’s list of the 100 Most Influential Companies of 2025 and identified by MIT Technology Review as one of the top 15 climate tech companies to watch in 2024. Pano AI has been featured in leading publications, including The Wall Street Journal, Bloomberg, and CNBC. The company serves dozens of government and enterprise customers across 16 U.S. states, five Australian states, and British Columbia, Canada, and currently monitors more than 50 million acres of land worldwide. It has raised $89 million in venture capital from investors including 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 Quality Engineer (Design) 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. What you’ll bring BS in Engineering (Mechanical, Electrical, Computer, Systems or related) or equivalent experience 7-10+ 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.

Full job record

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Org IDefca0d25-9b03-4658-9d97-f77fccead69b
Source ID42564cd3-4567-4ad3-b189-37b21b8c14ea
Board ID42564cd3-4567-4ad3-b189-37b21b8c14ea
Providerashby
Provider Job Key75ceb648-84b1-40ba-8b9f-a3f818a2a36a
TitleSenior/Staff Design Quality Engineer
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco, California
DepartmentOperations
TeamOperations
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySan Francisco
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://jobs.ashbyhq.com/pano-ai/75ceb648-84b1-40ba-8b9f-a3f818a2a36a
Apply URLhttps://jobs.ashbyhq.com/pano-ai/75ceb648-84b1-40ba-8b9f-a3f818a2a36a/application
First Seen At2026-05-29 06:18:31Z
Last Seen At2026-06-06 20:02:40Z
Last Checked At2026-06-06 20:02:40Z
Last Changed At2026-05-29 06:18:31Z
Inactive At
Source Posted At
Source Updated At
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Extensions
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Native Structured
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