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Product & Data Engineer (£50,000 – £90,000 + Equity) at BlakBear

Summary

Builds scalable GCP pipelines, APIs, and full-stack solutions to process real-time sensor data and AI-driven food-freshness predictions for supply-chain efficiency.

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.

See also

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