Product Engineer

About Axiom Axiom is building the translational intelligence layer for drug discovery: AI systems that help scientists predict human toxicity earlier, more accurately, and more mechanistically than animal studies or legacy in vitro assays. Unexpected toxicity is one of the largest reasons drug programs fail. Today, drug discovery teams still rely on fragmented assays, animal studies, and expert judgment to decide which molecules are safe enough to advance. We believe this can be dramatically improved. At Axiom, we generate and curate massive multimodal datasets spanning chemical structures, primary human cell imaging, multicellular tissue systems, transcriptomics, proteomics, mass spectrometry, ADME, dose-response curves, clinical outcomes, and human exposure. To date, we have created the largest experimental-to-clinical dataset in the world and we are just getting started. We use these datasets to train models and agents that connect chemistry, biology, mechanism, and clinical risk. We are looking for a product engineer to design and build the interfaces through which scientists actually use this intelligence. You will own the customer-facing agent and product, the internal research tools, and the design system that help Axiom’s models become useful in real drug discovery decisions. This is a role for someone who can build beautiful, powerful software for extremely complex scientific workflows. Charter Design and ship the first products that replace lab and animal toxicity experiments with accurate AI — while also building the next generation of internal tooling for ML research, data exploration, and scientific reasoning. You will help build products like: And then push far beyond them. What you will do You will own critical parts of Axiom’s product experience across customer-facing software, internal research tools, scientific data visualization, and design. You will: Lead development of Axiom’s reasoning agents and customer-facing product for exploring compound toxicity predictions, biological mechanisms, raw data, model outputs, and experimental evidence. Architecture agentic workflows which reason over a massive amount of biochemical data to predict human outcomes. Build internal tools that help ML researchers, computational biologists, chemists, and wet-lab scientists explore data, debug models, evaluate predictions, and move faster. Design and implement interfaces for complex scientific data, including dose-response curves, Cmax/exposure risk curves, high-content imaging, transcriptomics, proteomics, mass spec, ADME, mechanistic evidence, nearest neighbors, and model uncertainty. Build web applications capable of processing, navigating, and visualizing massive biological and chemical datasets. Architect full-stack product systems across frontend, backend, data access, auth, deployment, testing, customer workspaces, and enterprise delivery. Own customer workspace workflows, including workspace creation, deployment, onboarding, maintenance, data loading, user access, and customer-specific configurations. Work directly with internal scientists and external pharma design partners to understand how drug hunters think, what they value, and how Axiom can help them make better decisions. Map user workflows from raw data to insight: what scientists need to see, what they need to trust, what they need to compare, and what action they need to take next. Design product flows that make advanced AI predictions feel interpretable, credible, and useful to medicinal chemists, toxicologists, DMPK scientists, and program teams. Build the internal tooling that lets Axiom researchers discover, inspect, and improve emerging biological AI capabilities. Own Axiom’s product design system, visual language, interaction patterns, and overall product craft. Help build the best scientific software our users have ever touched. What we are looking for We are looking for a product engineer with exceptional taste, strong full-stack ability, and deep curiosity about science. You might be a great fit if: You have simplified extremely complex workflows with great software. You have built products that make dense data feel clear, navigable, and actionable. You are a full-stack engineer with a strong frontend/product orientation — roughly 70% frontend, 30% backend. You care deeply about visual design, interaction design, product quality, and performance. You have deep pride in the software you have built. You can work with a massive amount of complex scientific data and still find the right abstraction. You are comfortable talking to scientists, ML researchers, chemists, biologists, and enterprise customers. You can keep up with a highly technical, sophisticated crowd while staying practical and product-minded. You are comfortable getting in over your head and figuring things out quickly. You are curious about how everything works: ML models, biological assays, chemistry, customer workflows, infrastructure, design systems, and the business. You want to build software that changes how science is done. The kind of person who thrives here Axiom is not a normal company, and this is not a normal product engineering role. We are looking for someone who wants to build the product layer for a new kind of scientific AI company. The data is complex. The users are world-class scientists. The workflows are not obvious. The product must be beautiful, powerful, trustworthy, and scientifically rigorous. The people who thrive here: Have extremely high agency. Move with urgency. Have exceptional taste. Care deeply about product craft. Can design and ship without waiting for perfect specs. Are curious enough to learn biology, chemistry, ML, and drug discovery. Can turn complex scientific workflows into simple product experiences. Are practical, unpretentious, and collaborative. Want to work directly with customers. Want to build tools that make researchers dramatically more powerful. Raise the bar for everyone around them. Want to build a generational company. We are looking for someone who could work at a top software company, but would not be satisfied there because they want to build something harder, weirder, more important, and more beautiful. #J-18808-Ljbffr