data engineer for real-time freshness prediction

Enfint; Greater London; On-site; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Equity

Job summary

BlakBear — спин‑оут Imperial College London, создаёт продвинутые газовые датчики и ИИ‑модели, прогнозирующие свежесть в реальном времени для замены датчиками печати сроков годности в цепочке поставок.

Ищем инженера по бэкенду для масштабируемых ETL‑пайплайнов, инфраструктуры на GCP и разработки полнофункциональных API на Python и FastAPI, совместной работы с CEO и CTO над внедрением LLM‑агентов и полнофункциональных функций платформы.

Qualifications

• Опыт разработки и развёртывания production‑grade сервисов на Python.
• Опыт создания полноценных полнофункциональных приложений и их развёртывания.
• Знание CI/CD процессов и автоматизации.
• Способность работать в кросс-функциональных командах и быстро обучаться.

Responsibilities

• Design and maintain scalable ETL pipelines and GCP cloud infrastructure for real-time sensor data and AI predictions
• Build and iterate on robust APIs using Python and FastAPI across the full product lifecycle from design to operation
• Collaborate with the CEO and CTO to implement agentic AI tools and full-stack features for the freshness-prediction platform
• Own the back-end infrastructure and data strategy
• Build scalable GCP pipelines, design high-performance APIs, and develop full-stack solutions.

Skills

Python production-grade

Full-stack shipping

CI/CD automation

Team collaboration

Curiosity

Tools

Python

FastAPI

GCP

CI/CD

APIs

Job description

Описание

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

Задачи

• Design and maintain scalable ETL pipelines and GCP cloud infrastructure for real-time sensor data and AI predictions
• Build and iterate on robust APIs using Python and FastAPI across the full product lifecycle from design to operation
• Collaborate with the CEO and CTO to implement agentic AI tools and full-stack features for the freshness-prediction platform
• Own the back-end infrastructure and data strategy
• Build scalable GCP pipelines, design high-performance APIs, and develop full-stack solutions.

Требования

• 2–8 Years of experience in software or data engineering
• Strong mastery of Python for production-grade services
• Proven track record of building and shipping full-stack applications
• Experience maintaining automated CI/CD pipelines
• Deep curiosity and desire to solve hard problems
• Nice to have: Startup experience, hands-on LLM agent frameworks.

Условия

• Equity
• London, UK