Senior Data Platform Engineer — AI-Powered Systems

Scale AI; Greater London; On-site; GBP 110,000 - 170,000; Full time

Job summary

Scale AI is building and evolving core data storage, streaming, caching, and indexing platforms to power world-class AI systems. You will lead the design and development of these foundations while coordinating with stakeholders across product and engineering teams.

The role emphasizes building scalable backend data infrastructure, mentoring teams, and driving improvements in tooling and development practices within a fast-growing AI-driven environment.

Qualifications

• 5+ years of full-time backend engineering experience.
• Experience building large-scale data storage, streaming, and warehousing systems.
• Proficiency with Kubernetes and public cloud offerings.
• Excellent communication and collaboration with stakeholders.

Responsibilities

• Drive the design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborating with cross-functional teams to define, design, and deliver new features.
• Proactively identifying opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
• Presenting technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.

Skills

Backend systems

Data storage

Streaming

Data warehousing

Kubernetes

Cloud platforms

Distributed systems

Team leadership

Communication

Tools

MongoDB

Postgres

Kinesis

Flink

Spark

ElasticSearch

Redis

Trino

Presto

Snowflake

Job description

Scale AI is building and evolving core data storage, streaming, caching, and indexing platforms to power world-class AI systems. You will lead the design and development of these foundations while coordinating with stakeholders across product and engineering teams.

The role emphasizes building scalable backend data infrastructure, mentoring teams, and driving improvements in tooling and development practices within a fast-growing AI-driven environment.