Lead Product Designer, AI for the Planet

About the role

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Pay

Our base salary range is $137,520 – $206,289, and in addition we have generous bonus plans to provide a competitive compensation package.

About the team

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. Read more at allenai.org/skylight.
• 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. Read more at allenai.org/olmoearth.

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.

What we believe

• The mission is the point. We're building AI for the planet: environmental conservation, food security, climate. If it’s important to you to work on problems with a positive impact on our planet and the world, you’re in the right place.
• Great products are built alongside users. We put weight in listening to users, sitting with partners, and working side by side with researchers. This team travels regularly to sit with the people using what we build, watch them work, and bring what we learn back into the product.
• Ship small, learn fast. Our users are tackling huge problems and need tools that genuinely help. The fastest way to build those tools is alongside them: ship something functional, learn from how they use it, iterate. We hold a high bar for what we put in front of users, and we move with urgency. When something breaks, we focus on understanding the system, not blaming individuals.
• In-person matters. A lot of the best work on this team happens in unscheduled hallway conversations. We're in the office most days because that's where the team is at its best.
• We hire for curiosity. The tools we use and domains we operate in will change over the years. The people who do well here are the ones who enjoy learning new things, a new domain, a new way of working, not the ones who have mastered a particular toolkit.
• Ideas get better when they're challenged. We make decisions by talking them through – asking questions, pushing back when something doesn't quite add up, and being open to changing our minds. Everyone here is still learning, and we like it that way.

Who You Are

We're looking for a designer with exceptional fundamentals and a very keen eye. Someone with deep experience shipping complex, data-heavy software products, who can look at a hard problem and draw on well-established patterns to get us to a strong design quickly. Much of what we're building has no precedent to borrow from, so you'll need to invent: distilling complicated research ideas into clear, intuitive experiences from scratch. Your process is grounded in research and evidence; you balance what users need, what the mission demands, and what's realistic to build. You reflect thoughtfully on how we work and are comfortable pushing for change.

Requirements

• 8+ years of professional product design experience in industry, focused on web applications and software products. You've worked side by side with product and engineering teams and shipped real products to real users.
• Bachelor's degree.
• Exceptional design fundamentals. You have a deep command of usability, user research, interaction design, information architecture, visual design, and design systems. You can articulate why a design works, not just that it does.
• Experience designing data-intensive applications: dense tables, charts, filtering and query interfaces, dashboards, monitoring and alerting, or analysis tools where users are making decisions from what they see on screen.
• A track record of taking products end to end. Framing the problem, running user research, exploring options, driving to a decision, seeing it shipped to external users, and continuing to refine it based on how people actually use it.
• You're using modern AI tooling (e.g., Claude Code, agentic workflows) to move faster and rethink how design gets done. Our product managers and designers regularly build working prototypes and submit PRs.
• You build the design foundation for the team. Systems, patterns, components, and tooling that help the whole team design and build faster together. You bring in new ideas and techniques, and you look for ways to strengthen the whole team’s craft, not just your own work.
• You learn new domains fast. Everything we build sits on top of ML, whether that's an analyst acting on vessel detections or a technical team training models and building agents on our platform. You'll need to get fluent enough to design for both, and to make concepts like training runs and evaluation metrics legible to non-experts.
• A portfolio demonstrating at least one software interface design project, submitted with your application.

Preferred qualifications

• Experience at small or growth-stage companies, where you own 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.
• A demonstrated track record of building and self-directed learning. For example: side projects, open-source contributions, writing, or talks.
• Awareness of how software interfaces get built. Familiarity with HTML, CSS, and TypeScript is appreciated. You don't need to be an expert, just fluent enough to collaborate closely with engineers and know what's possible.
• Open to occasional international travel to meet directly with the people using what we build.

Projects We’re Excited About

To give you a better idea of the kinds of projects we work on, here are some examples of our current and past projects:

• Automated model development: We're building the OlmoEarth Platform to enable users to go from raw data to a fine-tuned, evaluated, production-ready computer vision model, without needing an ML engineer. That means designing for the entire loop: managing and inspecting datasets, making sense of complex model configurations, reading evaluation results, and deciding what to change on the next iteration. And once a model is running, how do we explain a prediction to someone who wasn't in the room when it was trained?
• Multi-tenant agents: We are building an agent-orchestration platform to power our next generation of AI products, starting with Shippy, our maritime-domain-awareness agent. This is an open design question we find genuinely exciting: what does a software product look like when you stop clicking through it and start asking it questions? We want our agents to show their work, so people can see how an answer was reached and decide whether to trust it. Figuring out how agents live inside a rich, interactive platform, rather than sitting off to the side in a chat window, is a big part of this role.
• Building confidence in our models: We use satellites like Sentinel-2, and Landsat to detect vessels globally in near-real-time, and we're expanding into other maritime conservation problems from the same imagery. How do we build trust with our users that our models work while also being transparent about when they don’t. How do we make precision and recall meaningful to someone who has never heard the terms, and who has to act on what we show them?

Physical Demands and Work Environment

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time.
• The ability to communicate information and ideas so others will understand.
• Must be able to exchange accurate information in these situations.
• The ability to observe details at close range.
• Can work under deadlines.