Senior AI Runtime Platform Leader

jobr.pro; Mountain View (CA); On-site; USD 228,600 - 297,120; Full time

Job summary

Databricks is seeking a Senior Engineering Manager to lead the AIR product team—owning both user-facing experiences and the underlying GPU training infrastructure. You will shape the roadmap, drive scalability, and coordinate across platform, product, infrastructure, and research groups to deliver high-impact, long-running training workloads.

You will mentor a high-performing team, emphasize reliability, observability, and performance, and partner with recruiting to attract top engineering

Qualifications

• 8+ years of software engineering experience, with 3+ years in engineering management.
• Track record building and operating managed GPU training infrastructure at scale (hundreds to thousands of GPUs).
• Deep familiarity with distributed training frameworks (PyTorch, DeepSpeed, Composer, Megatron-LM) and parallelism strategies.
• Experience with training resilience patterns: checkpointing, elastic training, and automated failure recovery for long-running jobs.
• Understanding of GPU performance fundamentals including NCCL, interconnect topologies, and memory optimization.
• Experience building platform products with clear SLAs and an owned customer experience.
• Strong cross-functional leadership and excellent collaboration across engineering, product, and research teams.

Responsibilities

• Lead, mentor, and grow a high-performing engineering team responsible for the Custom Training product and its foundational infrastructure, including distributed training orchestration, cluster lifecycle, fault tolerance, and training efficiency.
• Define and own the product and technical roadmap for AIR, balancing customer experience, functionality, and foundational investments.
• Collaborate closely with product, research, platform, infrastructure teams, and customers to drive end-to-end delivery, from ideation and prioritization to launch and operation.
• Drive architectural decisions and product design for managed GPU training at scale.
• Advocate for customer needs through direct engagement, ensuring engineering decisions translate to clear product impact.
• Build observability and reliability practices for long-running, multi-node training jobs, including checkpoint strategies, failure recovery, and operational runbooks.
• Partner with recruiting to attract, hire, and develop top-tier engineering talent.

Skills

GPU training infra

Distributed training frameworks

Platform product ownership

Cross-functional leadership

Performance optimization

Reliability & observability

Team recruiting collaboration

Education

BS/MS in CS/EE or related field

Job description

Databricks is seeking a Senior Engineering Manager to lead the AIR product team—owning both user-facing experiences and the underlying GPU training infrastructure. You will shape the roadmap, drive scalability, and coordinate across platform, product, infrastructure, and research groups to deliver high-impact, long-running training workloads.

You will mentor a high-performing team, emphasize reliability, observability, and performance, and partner with recruiting to attract top engineering