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Salary: GBP 115,000 - 135,000 / annual
Delos Data is a venture-backed startup building foundational technology to address performance, scalability, and resiliency challenges in large-scale AI data center clusters. The company is led by experienced founders and operators with successful track records, and is headquartered in Silicon Valley with operations across the US, Canada, and UK.
You will serve as the dedicated technical owner for a strategic customer's production deployment of Delos Data's software, embedded within their AI data center environment. This is a hands-on role combining customer success, field engineering, and product feedback loops.
Key Responsibilities:
- Serve as the primary technical owner for a strategic customer's production deployment, working hands-on in their AI data center environment (GPU/XPU clusters, high-speed fabrics, schedulers, orchestration).
- Lead integration, troubleshooting, performance tuning, and root-cause analysis for production issues.
- Guide customers through software upgrades, cluster expansion, and feature rollouts.
- Build runbooks, integration guides, and automation tailored to the customer's environment.
- Develop deep working relationships with the customer's infrastructure, SRE, and platform engineering teams.
- Translate customer problems into clear technical requirements and collaborate with the engineering team to design and deliver new features.
- Write and test production-quality code (Python, Bash, APIs) to prototype fixes, integrations, and tooling in the field.
- Feed structured insights on bugs, feature gaps, and competitive needs back to product and engineering; align customer milestones with product release cycles.
- Contribute hands-on technical work to RFPs, RFIs, technical evaluations, and proof-of-concept deployments for new customers.
- Help build reference architectures, demo environments, and technical collateral; represent the company at customer briefings, technical workshops, and industry events.
Requirements:
- 5+ years in a hands-on infrastructure engineering role (forward deployed engineer, SRE, platform engineer, solutions architect, or similar) with direct customer or internal-customer exposure.
- Proven AI data center experience: deploying and operating GPU/XPU clusters with high-speed interconnects (InfiniBand/RoCE/Ethernet/NVLink), job scheduling, and training/inference workloads.
- Strong software problem-solving skills, including debugging complex distributed systems and writing production-quality scripts and tools in Python and Bash.
- Hands-on experience with AI infrastructure software such as Kubernetes, Slurm, Tinkerbell, Canonical MaaS, observability stacks, or infrastructure management platforms.
- Deep proficiency with Linux, containers, and APIs.
- Track record of working with engineering teams to define and ship features based on field needs.
- Clear communicator, comfortable whiteboarding with SREs and briefing senior infrastructure leaders.
- Willingness to work on-site with the customer and travel as needed.
- Bachelor's or Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
Desired Skills:
- Experience as a forward deployed or embedded engineer dedicated to a single large customer.
- Experience taking early-stage or pre-launch products into hyperscale, neocloud, or AI lab environments.
- Familiarity with inference serving and performance optimization (e.g., KV-cache behavior, disaggregated serving, GPU utilization analysis).
- Background with observability stacks (Prometheus, Grafana, OpenTelemetry) and data pipelines for infrastructure analytics.
- Prior experience at an AI infrastructure software vendor, GPU cloud provider, networking vendor, or hyperscaler.
