Staff Data Engineer

Harnham
London, England
4 months ago
Applications closed

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DATA ENGINEER

LOCATION: London or Paris (remote-first with occasional meets)

SALARY: €120,000 + Equity


Shape the future of AI safety by building data pipelines at massive scale. Your work will power innovation across research and production.


THE OPPORTUNITY


The company is a fast-growing AI safety organization focused on building the reliability and optimization layer for AI systems. Its core platform uses natural-language policies to define what AI models should and shouldn’t do, automatically testing and enforcing these rules at scale.


Backed by $11M in funding from leading investors and senior figures at major AI and tech firms, the company processes over 100 million API calls monthly. It also fine-tunes and trains its own large language models to deliver faster and more cost-effective performance than open or proprietary alternatives.


The team is small, highly focused, and committed to solving hard problems with real-world impact. Employees work in a collaborative environment where ideas ship quickly to production and directly influence the future of AI safety.


ROLE AND RESPONSIBILITIES


This role focuses on designing and building scalable data pipelines and environments to handle petabytes of logs, events, and model outputs. You’ll develop internal APIs and tools that enable engineering and research teams to access data seamlessly without infrastructure complexity.


Key responsibilities include optimizing performance for analytics workloads and enforcing governance, permissions, and security policies. Strong proficiency in SQL and Python is essential, along with experience in modern data stacks such as Snowflake, ClickHouse, and event-streaming technologies. Familiarity with dashboarding tools like Metabase or Tableau is a plus.


This is an opportunity to make a significant impact in a fast-paced, AI-driven environment with a competitive salary, equity, and relocation support.


INTERVIEW PROCESS


  1. CV review and introductory conversation
  2. Technical interview – deep technical discussion
  3. Product interview – communication and collaboration with ML teams


Apply today and be part of shaping the future of AI safety.

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