Senior Engineer, Storage Services

Nscale is the GPU cloud engineered for AI, providing infrastructure for AI start-ups and large enterprises. They are seeking a Senior Engineer, Storage Services to lead technical direction and architecture for storage solutions, ensuring integration with the broader platform.

Responsibilities:

• Provide technical leadership across the Storage Services group for Block, File, Parallel, and Object storage services
• Lead the design of scalable, resilient, and high-performance storage solutions aligned with Nscale’s wider platform architecture
• Guide key engineering decisions, review designs, and uphold high standards of technical quality across the storage estate
• Drive architectural consistency, sound engineering practices, and strong technical governance across storage services
• Work closely with engineering leadership to translate storage strategy into clear technical plans, priorities, and implementation approaches
• Influence the roadmap by clarifying technical trade-offs, platform dependencies, and long-term architectural considerations
• Identify technical risks, scalability constraints, and operational weaknesses before they become larger issues
• Partner with engineers across platform, infrastructure, and product teams to ensure storage services integrate effectively into the broader Nscale platform
• Support teams with hands-on guidance to solve complex engineering challenges
• Contribute deep technical expertise where platform-level coordination and alignment are required
• Lead technical investigations, proof of concepts, and design work for new storage capabilities, service improvements, and platform enhancements
• Support the team in improving service reliability, observability, performance, supportability, and operational maturity
• Contribute to major incident resolution, root cause analysis, and continuous improvement where deep storage expertise is required
• Stay current with developments in storage technologies and distributed systems to inform decisions on tools, architectures, and service evolution
• Mentor and support engineers within the Storage Services group, helping raise technical capability across the team
• Act as a senior technical authority by reviewing implementation approaches and guiding teams through difficult technical problems
• Help set engineering standards that strengthen the quality and long-term maintainability of storage services

Requirements:

• Proven experience in a Principal Engineer, Staff Engineer, Lead Architect, or similar senior technical role within storage, cloud infrastructure, distributed systems, or platform engineering
• Deep expertise across modern storage architectures, including Block, File, Parallel, and Object storage systems
• Strong track record of leading technical direction in complex engineering environments without formal people management authority
• Demonstrable experience designing and operating large-scale, production-grade storage or infrastructure services
• Deep understanding of distributed systems principles, including performance, availability, consistency, fault tolerance, and scalability
• Experience working on platform-level services that support multiple products, teams, or customer use cases
• Strong systems thinking with the ability to evaluate trade-offs across architecture, operations, cost, performance, and customer requirements
• Hands-on engineering credibility with the ability to go deep into technical design, review implementation approaches, and guide teams through complex problems
• Experience mentoring engineers and raising technical standards across a team or organisation
• Strong communication skills with the ability to explain complex technical concepts clearly and influence stakeholders across engineering and leadership teams
• Comfort operating across both strategic and detailed technical work, from long-term architecture through to practical delivery guidance
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Experience in AI, HPC, data-intensive, or performance-sensitive environments would be highly advantageous