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DatabricksDatabricksSan Francisco, CA

Staff Backend Software Engineer- (AI Platform)

Staff Backend Engineer building and scaling Databricks Foundation Model Serving APIs for frontier LLMs (Llama, Claude, GPT). Design high-throughput low-latency GPU inference systems, influence architecture, and mentor teams. 10+ years large-scale distributed systems experience required; no prior ML/AI needed.

192k – 260k/yr
On-site10+ YOEBackend Engineering

About the role

Impact

  • Design and implement core systems and APIs that power Databricks Foundation Model Serving, ensuring scalability, reliability, and operational excellence.
  • Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads.
  • Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for GPU serving workloads.
  • Contribute directly to key components across the serving infrastructure — from working in systems like vLLM and SGLang to creating token based rate limiters and optimizers — ensuring smooth and efficient operations at scale.
  • Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems.
  • Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance.
  • Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy.

Requirements

  • 10+ years of experience building and operating large-scale distributed systems.
  • Experience leading high-scale operationally sensitive backend systems.
  • A track record of up-leveling teams engineering excellence.
  • Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems.
  • Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value.
  • Strong communication skills and ability to collaborate across teams in fast-moving environments.
  • Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.
  • Passion for mentoring, growing engineers, and fostering technical excellence.

Nice-to-Haves

  • Interest in building LLM APIs and runtimes at scale.
  • Experience with systems like vLLM and SGLang.
  • Experience with GPU workloads, token based rate limiters, and optimizers.

Skills

Distributed SystemsSystem Designlow-latency servingvLLMsglanggpu workloadsAPIsAlgorithmsData Structuresautoscaling
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