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Design and lead Databricks' next-generation network infrastructure, building scalable, multi-cloud connectivity platforms that power millions of VMs and enterprise security features.
Designs and secures cloud infrastructure for highly regulated public-sector environments, automating IAM, access policies, and audit logging across AWS, Azure, and GCP while ensuring FedRAMP/GovCloud compliance.
Designs and builds scalable backend systems for a data/AI platform used in sovereign and air-gapped cloud environments, primarily in Java, Scala, or Go.
Leads high-visibility security compliance initiatives for a cloud-native data platform, coordinating cross-functional teams to achieve federal authorizations like FedRAMP and DoD IL5/IL6.
Architect and lead the development of an AI-native platform that orchestrates agentic workflows for customer support and other enterprise domains using distributed systems and multi-cloud infrastructure.
P-1495 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of…
Builds and scales the core infrastructure for AI platforms at Databricks, including MLflow, AI Gateway, and model serving systems, using Scala, Go, or Python.
Designs and deploys GenAI models and systems for Databricks’ AI-powered products like Assistant and AI/BI Genie, focusing on LLM quality and scalable ML pipelines.
Build and scale Databricks' managed GPU training platform (AI Runtime), designing systems for large-scale AI model training, fault tolerance, and developer experience.
Designs and scales Databricks' next-generation AI-powered search platform, combining vector, keyword, and hybrid retrieval to power enterprise knowledge management and AI applications.
Designs and builds scalable backend services for Databricks' Lakehouse Platform, focusing on reliability and performance for data infrastructure in London.
Builds and scales the unified API layer for large language models at Databricks, enabling real-time and batch inference for enterprise customers using partner and self-hosted models.
Build and scale LLM inference infrastructure for enterprise AI workloads, enabling customers to serve and optimize frontier models with high reliability and performance.
Build and lead AI-powered internal platforms at Databricks, defining technical strategy and mentoring engineers to drive business growth.
Leads cross-functional programs to improve the reliability, performance, and operational excellence of Databricks' multi-cloud infrastructure, partnering with senior engineering leaders to set strategy and execute multi-quarter initiatives.
Lead the architecture and optimization of Databricks' GenAI inference engine, focusing on high-throughput, low-latency LLM serving across GPUs and accelerators.
Designs and optimizes low-level GPU kernels for AI inference, focusing on performance, correctness, and hardware efficiency while mentoring engineers and collaborating with ML teams.
Leads high-impact platform programs at Databricks, aligning engineering, product, and go-to-market teams to deliver scalable solutions for enterprise customers using cloud platforms.
Design and build AI-native, agentic systems for HR workflows like onboarding and analytics using Python, LangGraph, and Databricks, integrating enterprise HR platforms such as Workday.
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