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Product & Data Engineer

BlakBearvia Jack & Jill· London, England, United Kingdom· £50,000–£90,000/yrEquityLicensed sponsor
Posted 3 Aug 2026 · Added 3 Aug 2026, 14:58
BlakBearR&D (eng/science)founded 2017
AI summary

You will own back-end infrastructure and data strategy, building scalable GCP pipelines, designing high-performance APIs with Python and FastAPI, and developing full-stack features with automated CI/CD. The company, an Imperial College spin-out, produces advanced gas sensors and AI that predict food freshness in real-time to replace printed expiry dates across global supply chains.

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Job Title

Product & Data Engineer

Salary

£50,000 – £90,000 + Equity

Company Description

BlakBear is an Imperial College London spin-out building advanced gas sensors and AI that predict food freshness in real-time, replacing archaic use-by dates across the supply chain.

Job Description

You will own the back-end infrastructure and data strategy for a mission-driven startup tackling global food waste. Working directly with the founders, you will build scalable GCP pipelines, design high-performance APIs, and develop full-stack solutions. Your work directly impacts how the world monitors food quality across global supply chains.

Location

London, UK

Why this role is remarkable

Join a high-impact mission to eliminate 1/3 of global food waste by replacing archaic printed expiry dates with real-time sensor intelligence.

Work in a high-caliber environment as an Imperial College London spin-out that is already signing enterprise contracts across Europe and North America.

Enjoy significant growth potential and ownership in a seed-stage team of under 20 people, directly influencing the product’s technical evolution.

What You Will Do

Design and maintain scalable ETL pipelines and GCP cloud infrastructure to process real-time sensor data and AI predictions.

Build and iterate on robust APIs using Python and FastAPI, managing the full product lifecycle from design to operation.

Collaborate with the CEO and CTO to implement agentic AI tools and full-stack features that enhance the core freshness-prediction platform.

The ideal candidate

Has 2–8 years of experience in software or data engineering with a strong mastery of Python for production-grade services.

Possesses a proven track record of building and shipping full-stack applications and maintaining automated CI/CD pipelines.

Exhibits deep curiosity and a desire to solve hard problems, ideally with experience in startup environments or hands-on LLM agent frameworks.