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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 100+ 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 TIME's 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
For this Software Engineer role, we’re looking for somebody who will drive major projects in unlocking new end-to-end capabilities for our users while building scalable, secure, and maintainable production systems. At Pano, team members take ownership of what they do, and our approach to problem-solving relies heavily upon creativity, communication, and collaboration.
The ideal candidate is humble, hungry, and people-smart. They have experience building backend solutions and a firm understanding of industry frameworks, APIs, databases, and multiple back-end languages, including Java and Python.
What you’ll do
- Work with your teammates to build highly scalable solutions that enable positive impact for our users and our business
- Develop new features as well as tools, frameworks, and workflows in support of rapidly emerging business and project requirements
- Drive new projects, from conceptualization to deployment
- Ensure application performance, uptime, and scale, and maintain high standards for code quality, maintainability, security, and application design
- Work with agile development methodologies, adhering to best practices and pursuing continued learning opportunities
- Participate in on-call rotation to respond to, triage, mitigate, and resolve production issues
- Create run-books, metrics, and dashboards
What you’ll bring
- 5+ years of hands-on experience as a backend Software Engineer
- 3+ years of professional experience in a fast-paced SaaS or a similar business environment
- Experience with server-side Java and Python software development, with modern frameworks and methodologies, such as Spring and Django
- Proficiency with SQL, RDBMS (ideally PostgreSQL), and familiarity with ORMs
- Ability to visualize a proposed system and be able to build it
- Proven ability to troubleshoot and resolve technical issues in complex systems
- Ability to communicate effectively within the team and across the organization while sharing insights and updates and collaborating to achieve project goals
- Must be located in the Pacific or Mountain time zone
Preferred skills
- Hands-on experience with cloud platforms, such as GCP and AWS
- Familiarity working with Linux-based systems as well as containerization and orchestration tools, such as Docker and Kubernetes
- Familiarity with caching mechanisms such as Redis, Memcached, and Varnish
- Familiarity with common DevOps tools and practices, such as Git and CI/CD
- Familiarity with SOC2 / ISO 27001 security frameworks
Pano is an equal opportunity employer committed to recruiting and supporting our team-members regardless of where they come from. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Pano San Francisco, California, USA Office
San Francisco, CA, United States
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
