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

For the Platform Engineer role, we’re looking for somebody who will drive major projects in how we scale, secure, and monitor our systems and services throughout the entire organization. At Pano, we strongly believe in allowing team members to take ownership of what they do, and our approach to problem-solving relies heavily upon creativity, communication, and collaboration.

We’re running large systems at scale and have a growing infrastructure footprint, so we are looking for an experienced engineer to run, develop, and enhance our platform. Someone with the wisdom and experience to build mature operational processes for the future but also comfortable with rolling up their sleeves, writing code, and building systems in a startup environment. Someone passionate about improving the development experience for engineers and providing guidance on what kinds of tools and workflows will remove barriers to get things done.

What you’ll do

• Collaborate with cross-functional teams to design, implement, and maintain scalable and reliable infrastructure

• Supporting and optimizing production systems as a Platform Engineer and development workflows as a DevOps Engineer

• Utilize Infrastructure as Code (IaC) principles to automate provisioning, configuration, and deployment processes

• Improve the release process through robust CI/CD pipelines to enhance software delivery efficiency

• Provide expertise in Cloud services and infrastructure, particularly in Google Cloud Platform (GCP)

• Troubleshoot and resolve complex technical issues related to infrastructure and deployment

• Actively contribute to evolving coding standards and best practices within the development team.

• Create run-books, metrics, and dashboards

• Participate in on-call rotation to respond to and triage production issues

What you’ll bring

• 5+ years of professional experience in a fast-paced SaaS or a similar business environment

• 3+ years of hands-on experience supporting production systems as a Platform Engineer, Site Reliability Engineer (SRE) or a DevOps Engineer

• 3+ years of hands-on experience with cloud services and technologies (GCP, AWS, Azure, etc.)

• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes)

• Proficient in Infrastructure as Code (IaC) tools and methodologies (e.g. Terraform, Pulumi, Puppet, etc.)

• Proven ability to manage, troubleshoot and resolve complex technical issues in distributed systems

• Ability to communicate effectively within the team and across the organization while sharing insights and updates and collaborating to achieve project goals

• Preferred skills:

  • Advanced working knowledge of GCP Services like GKE, GCS, IAM, etc.

  • Professional experience supporting AI and ML infrastructure and familiarity with the ML development lifecycle

  • Experience with MLOps tools for model serving/inference and observability

  • Strong software development, particularly with scripting languages (e.g., Python, Bash, etc.)

  • Experience with system administration in general and Linux in particular

  • Familiarity with SOC2 / ISO 27001 security frameworks

• Preference for someone in the Pacific / Mountain time zone

Final compensation for regular 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, regular full-time roles are eligible for equity. Benefits are tailored to local market standards and statutory requirements in the employee's country of employment, and may include health coverage, retirement or pension contributions, and paid time off. Specific benefit details will be shared during the interview process.