Risk and Resilience R&D Lead, Applied AI 21

Class 3 Technologies is hiring a Risk and Resilience R&D Lead, Applied AI, based in Maryland, with a hybrid work model (SF Bay Area or NYC). The role involves developing engineering-based models to quantify climate hazards' impact on infrastructure, designing AI workflows, and collaborating on model deployment within their climate risk analytics platform, Iris. Ideal candidates have a strong engineering background in hazard modeling and AI applications.
Risk and Resilience R&D Lead, Applied AI - Class 3 TechnologiesLocation:
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.