Risk and Resilience R&D Lead, Applied AI – Class 3 Technologies

Location: US-based (SF Bay Area or NYC, Hybrid)

Type: Full-time

Reports to: CEO

Compensation: $150,000–$175,000 base (depending on experience and location) + equity

About Class 3 Technologies

We’re building the foundation of climate resilience.

Class 3 Technologies was born to protect organizations from natural hazards and climate change. Our mission is to bring clarity where there’s confusion — giving enterprises, institutions, and investors the intelligence to turn climate risk into resilience.

Each year, natural disasters cause tens of billions of dollars in losses across the United States alone. As storms, wildfires, floods, heatwaves, and earthquakes intensify, the human and economic toll continues to rise. Codes can safeguard lives, but not the systems that sustain them. True resilience keeps communities standing — and functioning — after disaster strikes.

Our platform, Iris, is the next generation of climate risk software. Where traditional tools stop at abstract scores or metrics that are not traceable, Iris predicts asset-level losses down to the building component, allowing our customers to defend high-stakes decisions and act with confidence.

Developed by engineers who’ve designed buildings to withstand disasters, Iris combines high-resolution hazard data with proprietary engineering-based damage models to simulate how assets perform under stress — and how to make them more resilient to meet the needs of their owners, operators, and communities.

We don’t stop at quantifying risk. We are here to reduce it.

The Role

Class 3 Technologies is seeking a  Risk + Resilience R&D Lead, Applied AI to advance the technical foundation of our climate risk analytics platform. In this role, you will help develop, refine, and validate engineering-based models that quantify how climate hazards affect buildings and infrastructure, translating physical impacts into actionable risk insights and resilience options for organizations, investors, and insurers.

A core part of the role involves designing and deploying agentic, AI-enabled workflows that accelerate model generation, calibration, and validation, enabling Class 3 to rapidly expand risk coverage across new asset types, hazards, and geographies.

Beyond model development, you will play a key role in bridging technical innovation and real-world deployment. This includes leading technical aspects of customer pilots, supporting platform deployments, and collaborating with product and engineering teams to operationalize new models within the Iris platform. You will also contribute to shaping Class 3’s modeling standards, research agenda, and technical roadmap, ensuring our methodologies remain scientifically rigorous, transparent, and defensible.

This role is ideal for someone with a strong engineering background in hazard and risk modeling who enjoys building new analytical capabilities, applying emerging AI techniques to complex risk problems, and helping translate technical models into scalable tools used by decision-makers managing climate risk.

About You

You've spent years working with the models that quantify physical risk. You understand how hazard models translate into vulnerability and loss estimates, and you've probably been frustrated by how rigor is often compromised at each step of the risk workflow.You want to build, not maintain. You're looking for a place where your modeling work directly contributes to the product, where you can see your damage functions running in production against real portfolios within weeks. You're fluent in Python and ML/AI methods, and you see agentic workflows as a way to dramatically expand and improve models without sacrificing engineering quality. It’s not just the future, it’s here, and you are eager to leverage it.

You're technical-first but not lab-bound. You are as comfortable writing the code as you are explaining what it’s doing to a layperson. You do this naturally because you understand the engineering, not because you rehearsed a script.

Physical climate risk might be personal for you. You want a stake in meaningfully reducing disaster risk globally, and you want your models to be used, not shelved. You don't settle for second-rate work. High quality is a pre-requisite. You are inquisitive and curious by nature. You are generous with sharing your knowledge. You take responsibility seriously but you give others grace.

You'll be the first dedicated R&D hire on a team with unusual technical density. You will be working directly with the CEO who has pioneered risk modeling and resilience-based design approaches. Most team members hold advanced degrees in engineering. You won't spend time educating colleagues on fundamentals. You’ll raise the bar. 

What You’ll Do

• Advance our risk and resilience models, including engineering-based vulnerability and loss models for buildings and infrastructure across multiple climate hazards.
• Develop agentic AI workflows to accelerate and enhance model generation, calibration against real world data, and expanding coverage to new asset archetypes, hazards, and geographies.
• Prototype and deploy AI/ML methods to develop predictive relationships between asset characteristics and hazard vulnerability.
• Evaluate and integrate new datasets (hazard, exposure, historical) to improve model fidelity and coverage.
• Help define Class 3’s modeling standards, technical roadmap, and research priorities.
• Build upon and expand our customer support infrastructure: knowledge base, onboarding SOPs, training materials, FAQs, and self-service resources
• Collaborate with engineering, product, customer success, and data teams to deploy the latest capabilities onto the Iris platform.
• Support pilots with prospective customers, and work with Customer Success to support existing customers on project deployments, technical training sessions, and technical support.
• Engage with academic research and industry best practices to keep Class 3’s methods scientifically rigorous and defensible.

What We’re Looking For

• Advanced degree (MS or PhD) in structural, wind, or seismic engineering
• 5–10+ years of experience developing or applying risk, vulnerability, or catastrophe models for buildings or infrastructure, across multiple perils
• Experience applying machine learning or AI methods to risk modeling, data extraction, or model calibration in practical applications
• Experience or interest in designing AI-assisted or agentic workflows to automate modeling, data processing, or analysis tasks
• Experience working with engineering-based or statistical models for natural hazards (e.g., FEMA P-58, HAZUS, or other models)
• Proficiency in Python or similar scientific computing environments for modeling, data analysis, and prototyping
• Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders
• Interest in building scalable analytics products rather than one-off consulting studies.
• Comfortable working in a fast-moving startup environment where priorities evolve and individuals often move between research, product development, and client-facing work

Bonus 

• Licensed Professional Engineer or EIT
• Experience with building design or analysis
• Familiarity with resilience-based design/engineering or practical adaptation applications
• Experience with developing agentic workflows for automation
• Knowledge of building codes and construction practices
• Experience in consulting or strategic advisory
• Experience in insurance or catastrophe modeling
• Familiarity with climate disclosure and reporting frameworks
• Familiarity with geospatial analysis tools (e.g., GIS, raster data, spatial modeling workflows).
• Experience working with asset-level exposure data such as building characteristics, property portfolios, or infrastructure inventories.
  
  

First 3 to 6 months

• Familiarize yourself with full software stack and risk and resilience models
• Improve, calibrate, and deploy Class 3’s vulnerability and loss models across multiple hazards
• Develop AI-assisted workflows that accelerate model generation, validation, and expansion to new asset archetypes and geographies.
• Support ongoing pilot and active deployments
• Deploy new modeling capabilities to the Iris platform in collaboration with engineering and product teams.
• Expand the internal modeling toolkit by integrating new datasets and machine learning approaches that improve predictive performance and analytical coverage.
  
  
  

Why Join Us

We're not chasing hype — we're building something that matters. At Class 3, you'll work with clients protecting real assets and real communities from real risks. You'll sit at the intersection of product, engineering, and some of the most sophisticated institutional real estate and investment teams in the world.

Most climate risk tools treat engineering as a black box. The models are opaque, the outputs aren't traceable, and the people building them rarely talk to the people using them. Class 3 exists because that's broken.

Iris was built by engineers who've designed structures to survive earthquakes, hurricanes, and floods. The platform's damage models are component-level, transparent, and grounded in real structural behavior. We're now scaling coverage across hazards, geographies, and asset types, and we need someone who can push the modeling frontier while helping bring that work to market.

You'll be the first dedicated R&D hire, helping define how modeling and AI capabilities scale across the platform. The models you build will ship. The workflows you design will define how the platform scales. And you'll do it on a team where engineering rigor isn't a talking point; it's the product. If you've been looking for that environment, this is it.

This is a rare opportunity at the intersection of risk and resilience and AI-enabled scaling. 

• Mission with tangible impact, not just metrics
• Early ownership and direct influence on product direction
• Flexible, remote-first work environment
• Competitive salary and equity
• Health, dental, and vision insurance
• 401(k)
• Flexible PTO

Class 3 Technologies is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive environment for all employees, regardless of race, gender, age, religion, identity, or experience.