Member of Technical Staff - Data Engineer

Dex; Greater London; Hybride; GBP 90 000 - 130 000; Plein temps

Résumé du poste

Dex is partnering with a seed-stage research lab in London/Paris to recruit a role that will own the data platform powering AI training environments. You will design, implement, and operate end-to-end ingestion, processing, and storage systems, focusing on production code and scalable architectures rather than dashboards.

You will build automated validation, sanitisation, and PII-redaction pipelines, making raw data immediately usable for AI training. Hybrid work from London or Paris is expected.

Qualifications

• Proven track record designing, shipping, and operating substantial production data systems end to end.
• Ability to debug complex, distributed failure modes in unfamiliar codebases.
• Experience with large, messy datasets and data ingestion bottlenecks.
• Capacity to define system architecture from ambiguous requirements and ship production systems.
• Hybrid work capability from London or Paris.

Responsabilités

• Architect and operate scalable ingestion, processing, and storage systems for high-volume datasets.
• Build automated validation, sanitisation, and PII-redaction pipelines for AI training data.
• Balance storage, latency, observability, reliability, and cloud costs with pragmatic trade-offs.
• Establish reusable data platform patterns for use by software and AI engineers.
• Debug production failures across the stack and deploy modern tooling to improve feedback loops.

Connaissances

Data platforms

Distributed systems

Data ingestion

PII sanitisation

Observability

Production debugging

Cloud cost awareness

Description du poste

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

The role

Training frontier AI agents requires interactive digital environments where models can act, fail, and learn across real software. In roughly a year, this seed-stage research lab has scaled to over 50 engineers across London and Paris, partnered with multiple frontier AI labs, and secured backing from top-tier investors and founders. The core constraint on agent performance is data: acquiring, sanitising, and reliably serving massive, messy real-world datasets to the engineers building those training environments.

You will own the data platform powering these environments end to end, from architectural design to production debugging. This is not a BI or reporting seat, and it is not an isolated pipeline-plumbing gig. You will work across software, platform, and AI engineering boundaries to build high-throughput ingestion, automated PII sanitisation, and validation engines, staying close to production code rather than just configuring vendor dashboards.

The work

• Architect and operate scalable ingestion, processing, and storage systems that handle messy, high-volume datasets from real-world software environments.
• Build automated validation, sanitisation, and PII-redaction pipelines that make raw data immediately usable for AI training environments.
• Make pragmatic technical trade-offs across storage, retrieval latency, observability, system reliability, and cloud costs.
• Establish reusable data platform patterns that other software and AI engineers can build on, eliminating the need to solve dataset ingest on an ad-hoc basis.
• Debug unfamiliar production failures across the stack and deploy modern tooling to keep engineering feedback loops tight.

What You Bring

• Proven track record designing, shipping, and operating substantial production data systems end to end, with personal ownership over the architectural decisions and outcomes.
• Strong software engineering fundamentals with the ability to dive deep into unfamiliar codebases and debug complex, distributed failure modes.
• Direct experience working through large, messy, or adversarial datasets where ingestion, validation, or sanitisation posed genuine technical bottlenecks.
• Demonstrated ability to take ambiguous requirements, define the necessary system architecture, and ship production systems without detailed functional specs.
• Based in or able to work hybrid from London or Paris.

As part of the recruitment process at Dex, we process your personal data in accordance with our Privacy Notice for Job Applicants. This notice explains how and why your data is collected and used, and how you can contact us if you have any concerns.