The role asks for hands on reliability engineering for a data platform that is scaling from terabytes to petabytes. A strong candidate brings practical experience running distributed systems in production, solid grounding in networking, operating systems and databases, and comfort with on call and incident work. The job also expects close collaboration with backend and machine learning engineers to improve deployment pipelines and reliability habits.
How it fits the AI era
AI changes the work by making data volume and pipeline complexity grow quickly, so capacity planning and performance tuning become central. Observability and incident response still depend on human judgment, especially when tracing failures across many services. The role stays human in setting reliability targets, leading blameless reviews and guiding teams toward resilient designs.
How it builds AI experience
The company handles video, sensor and image data for physical AI systems, so the role offers exposure to infrastructure that supports large scale training and supervision data. Building AI experience means learning how storage, compute and networking behave under petabyte scale pipelines and how observability covers machine learning workloads. It also means practicing capacity planning for data heavy services and reviewing automation that supports AI teams.
Worth showing
- Production SRE experience
- Observability tooling
- Kubernetes and cloud
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
About Encord
A data platform that helps AI teams manage, label and clean the video, sensor and image data that trains robots, self-driving cars and other physical AI systems.
Senior SRE Engineer employer: present of AI
H Company is an exceptional employer for Product Designers, offering a dynamic work environment in London where innovation meets collaboration. With a strong focus on employee growth, the company encourages continuous learning and experimentation, particularly in the evolving field of AI design. The inclusive culture fosters open communication with users and cross-functional teams, ensuring that every designer's voice is heard and valued, making it a truly rewarding place to advance your career.
