Lead Product Designer, AI for the Planet

The Allen Institute for Artificial Intelligence•Seattle, WA

2d•Onsite

About The Position

We are a small product team at the Allen Institute for AI working on AI for the Planet. We're working on maritime conservation, food security, disaster resilience, and climate solutions with some of the most impactful organizations on the planet. Design, engineering, product, and partnerships work side by side with an ML research team, building products that support our environmental and high-impact users. Today, our team works on two products: Skylight provides AI-powered intelligence to combat illegal, unreported, and unregulated fishing to protect our oceans. Governments, enforcement agencies, and conservation organizations in 95+ countries use Skylight data to protect their waters today via our interface, API, and most recently an agentic interface named Shippy. OlmoEarth is an open platform built around our family of foundation models for Earth observation. Users create custom fine-tuned models to detect and classify novel geospatial features. The platform handles the full loop: imagery acquisition, annotation, as well as model training and inference for ML and non-ML experts alike. Partners today include International Food Policy Research Institute, The Group on Earth Observation, NASA Harvest, Global Mangrove Watch, Amazon Conservation Alliance and more across for-good domains. You'll own the design for these products, and you'll have designers around you. Ai2's design group spans the organization, with designers working on open models, scientific agents, and our other conservation platforms. We lean on each other for critique, shared systems, and solving hard interaction problems. It's a small group, so the patterns you set here influence other teams and products. If you're the kind of designer who is excited by how fast the craft is changing and wants your work to support for-good efforts in agriculture, ocean conservation, forests, and the climate, this is for you.

Requirements

8+ years of professional product design experience in industry, focused on web applications and software products.
Experience working side by side with product and engineering teams and shipping real products to real users.
Bachelor's degree.
Exceptional design fundamentals: deep command of usability, user research, interaction design, information architecture, visual design, and design systems.
Ability to articulate why a design works.
Experience designing data-intensive applications (dense tables, charts, filtering and query interfaces, dashboards, monitoring and alerting, or analysis tools).
Track record of taking products end to end: framing the problem, running user research, exploring options, driving to a decision, seeing it shipped, and refining based on usage.
Experience using modern AI tooling (e.g., Claude Code, agentic workflows) to move faster and rethink design.
Ability to learn new domains quickly, including ML concepts.
A portfolio demonstrating at least one software interface design project.

Nice To Haves

Experience at small or growth-stage companies, owning outcomes end to end without heavy process scaffolding.
Experience designing for varying user groups: non-technical people acting on AI output, non-English speakers, or users on low-bandwidth connections.
Experience with geospatial interfaces (maps, layers, time sliders, spatial querying).
Demonstrated track record of building and self-directed learning (e.g., side projects, open-source contributions, writing, or talks).
Awareness of how software interfaces are built.
Familiarity with HTML, CSS, and TypeScript.

Responsibilities

Own the design for AI for the Planet products.
Build the design foundation for the team, including systems, patterns, components, and tooling.
Bring in new ideas and techniques to strengthen the whole team's craft.
Design for the entire loop of automated model development, including managing and inspecting datasets, understanding model configurations, reading evaluation results, and iterating.
Design multi-tenant agents, including how they live inside a rich, interactive platform.
Design systems to build user trust in AI models while being transparent about their limitations.
Explain AI predictions and concepts like training runs and evaluation metrics to non-experts.
Collaborate closely with product managers and engineers.
Travel occasionally to meet directly with users.