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.
The role
Most AI systems train on static data. This lab builds resettable, interactive digital environments where frontier AI agents learn by actively operating real software, failing, and iterating. Behind these environments sits a massive engineering bottleneck: ingesting, sanitising, and serving large, chaotic real-world datasets so models can train on them reliably. Backed by top-tier investors and collaborating closely with leading AI research labs, they are early enough that foundational data architecture is still being built from scratch rather than maintained.
You will join as a Member of Technical Staff owning core data systems from initial problem definition through production operations. This is not a business intelligence or dashboarding role, nor is it a hands-off architecture seat or pipeline-wrangling gig configuring off-the-shelf tooling. You will write production code, debug complex distributed systems across platform and AI engineering boundaries, and design the validation, sanitisation, and ingestion infrastructure powering next-generation agent training.
The work
- Architect, build, and operate scalable distributed systems to acquire, ingest, and process massive, unstructured datasets for agent training environments.
- Design and implement automated data quality, validation, sanitisation, and PII-handling pipelines resilient to adversarial and messy real-world data.
- Make foundational trade-offs across storage tiers, query performance, reliability, observability, and infrastructure cost without being tied to a fixed vendor stack.
- Partner directly across platform, software, and AI research teams to establish platform-wide architectural patterns rather than solving dataset problems as one-off tickets.
What You Bring
- Proven track record of owning substantial production data systems end to end, with clear personal accountability for architecture, implementation, and operational outcomes rather than just configuring existing ETL tools.
- Strong, recent hands‑on software engineering fundamentals, with the ability to go deep into unfamiliar codebases and debug distributed systems failure modes.
- Demonstrated experience tackling large, complex, or messy datasets, with the ability to articulate exact failure modes, trade-offs, and architectural alternatives.
- Comfort operating in high ambiguity: taking an unformed problem, deciding what to build, and executing without a detailed specification.
- Based in or willing to work with engineering teams in London or Paris.
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Member of Technical Staff - Data Engineer (up to £200k) employer: Dex
At Dex, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London-based team enjoys a hybrid working model, competitive benefits, and ample opportunities for professional growth, all while contributing to cutting-edge technology in the healthcare sector. Join us to make a meaningful impact in real-time systems and edge deployment, surrounded by a supportive team dedicated to excellence.
