Product Engineer

present of AI; Greater London; Hybrid; GBP 65,000 - 95,000; Full time

Job summary

present of AI in Greater London seeks a Product Engineer who blends software development with close attention to what scientific and industrial users actually need. You’ll build reliable interfaces and workflows around AI model outputs, collaborating with researchers and engineers to ship usable features.

You’ll turn fuzzy requirements into concrete functionality, perform practical testing with real users, and contribute across the stack.

Qualifications

• Experience in full stack product engineering.
• Comfort with technical users to gather feedback.
• Ability to translate fuzzy requirements into working features.
• Grounding in science or data helpful for design decisions.
• Experience shipping AI-backed features or AI-enabled workflows.

Skills

Full stack product engineering

Working with technical users

Turning requirements into features

Science or data grounding

Shipping AI backed features

Job description

A Product Engineer in this setting typically combines software building with close attention to what scientific and industrial users actually need. A strong candidate brings solid full stack or product engineering skills, comfort working with technical users, and the ability to turn fuzzy requirements into working features. Given the company's focus on turning wanted material properties into synthesizable designs, some grounding in scientific or engineering data helps.

How it fits the AI era

AI is the core of the product here, so the engineering work sits close to models that propose chemical designs. The role changes by making it easier to build interfaces and workflows around those model outputs, while judgment about what users need and what makes a result trustworthy stays human. Clear thinking about product tradeoffs and careful testing remain central.

How it builds AI experience

Working here offers hands on exposure to AI driven scientific discovery, from how model outputs are surfaced to how users judge and act on them. A candidate can build this by shipping features that use AI outputs, learning enough about the science to ask good questions, and showing examples of products built around model results.

Worth showing

• Full stack product engineering
• Working with technical users
• Turning requirements into features
• Science or data grounding
• Shipping AI backed features

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About CuspAI

An AI search engine for new materials that the company says turns a wanted set of physical properties into synthesizable chemical designs in months instead of years of lab trial and error.