Are you a senior product builder who likes shipping things that matter? We're looking for an experienced technical generalist to join us and help build the next generation of our impact data products, end-to-end, across the stack, with real users on the other side.

At Upright, you get to work on a product that actually matters: the world's largest open-access database on company impact, used by 1,000+ institutional investors and corporations to make real capital allocation decisions. We quantify companies' impact from the ground up, based on peer-reviewed science and what companies actually produce and sell. The raw material is their product data, which we collect and classify automatically at scale.

A few things our team has built recently:

• A global physical climate-risk model for any company. We built a pipeline that pulls in open scientific datasets on heat stress, wildfires, and coastal and riverine flooding, projects them onto a worldwide grid of ~145 million points under both moderate and high-emissions scenarios, and turns the raw data into per-location risk scores. Customers can now see, for any company they hold or are considering, how exposed its real-world locations are to physical climate hazards today and out to 2050.
• Automatic discovery of a company's real physical footprint. An AI agent that, given just a company name, finds its actual sites, headquarters, factories, data centres, stores, warehouses and pins them to real coordinates. This means our impact and climate-risk numbers are computed against where a company actually operates, instead of falling back on country averages.
• An LLM-assisted Double Materiality Assessment engine that automates a process consultants currently charge €50–200k for, with structured outputs, retrieval over peer-reviewed evidence, and a custom eval harness keeping quality measurable.

As a Product Builder, you'll own larger product areas end-to-end: from the schema and business logic in the backend, through the data and LLM-assisted pipelines that produce the numbers, to the UI where users actually see them. You'll work closely with our sustainability and domain experts to turn fuzzy, expert-led requirements into shipped features, and you'll have real authority over the technical direction of the areas you own. Your specific responsibilities will be tailored during the recruitment process to your background, skill level, and interests. If you're ready to grow your career while building a platform that matters and to do it in an AI-forward engineering environment, we'd love to hear from you!

SIGNS FOR BEING A GREAT MATCH:

At least 4 years of professional experience in software engineering or a closely related technical field.

Strong track record of shipping product features end-to-end, backend, data, and UI, and operating them in production. Python and TypeScript are our primary languages.

Strong generalist instincts: you move comfortably between backend services, data, and LLM-assisted pipelines, and the UI, and you pick up new domains quickly.

Comfortable collaborating closely with non-engineering domain experts (sustainability researchers, analysts, customers) and turning expert judgment into structured, shippable software.

Strong output orientation and common sense thinking to enable solving hard-to-define problems, as well as the ability to see the big picture and prioritize work accordingly.

Strong analytical thinking. You reach for the right tool (a well-designed service, a clean schema change, an LLM-assisted step, or just a well-placed SQL query) instead of defaulting to one.

Eager to work with LLM-assisted features, prompts, structured outputs, retrieval, evals, even if you don't consider yourself an ML specialist. Bonus if you already work with coding agents (Claude Code, Cursor, etc.) day to day.

Solid track record of internal passion for excellence: you have gotten things done clearly better than what was required, because you enjoy doing things well.

ADDITIONALLY, WE VALUE:

Experience designing and operating production data pipelines, or contributing meaningfully to ones owned by others.

Hands-on experience with LLM-assisted systems: prompt design, structured outputs, retrieval, agentic tool use, and building evals that catch regressions.

Comfort with applied statistics, predictive modeling, or other quantitative methods.

Experience with cloud infrastructure such as AWS (ECS, Fargate, SageMaker, Glue, ECR) or equivalents in GCP / Azure.

Experience contributing across the stack, backend, data, and occasionally frontend or infra, in a small, fast-moving team.

WHAT WE OFFER:

A chance to join a quickly growing and highly ambitious impact SaaS company with a mission that matters — real capital allocation decisions at 1,000+ institutional investors and corporations rest on the data we build.

A team of exceptional people who are kind, direct, and care deeply about doing the work well.

An unusually AI-forward environment — first-class tooling, in-house agents, and the freedom to keep pushing what "AI-native development" actually means in practice. You'll be shaping the workflow, not inheriting it.

Substantial autonomy and ownership from day one, with lots of room to grow.

Competitive compensation, including stock options and a comprehensive healthcare package.