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Build and maintain scalable backend services and infrastructure for Databricks platform. Work on distributed systems, storage integrations (S3/Azure Blob), SaaS/service-oriented architectures, data pipelines (Spark), monitoring, and high-performance client libraries to support large-scale workloads.

Lead search quality for both LLM agents and human users by building and optimizing hybrid retrieval, ranking models, and evaluation frameworks across structured and unstructured data to ensure high-precision, high-recall results.

As a Staff Software Engineer in Observability at Databricks, you'll develop observability solutions for product and infrastructure health, manage cloud infrastructure, improve monitoring practices, and mentor other engineers.

Perform inbound and outbound prospecting to build pipeline, partner with sales to develop territory strategy, identify Databricks use cases to grow consumption, and deliver a strong customer experience through solution-focused outreach and follow-up.

Solutions Architects lead the adoption of Databricks' platform, consult on big data architecture, and develop solutions for customers. This role involves technical leadership, prototyping, and building reference architectures while collaborating with sales and technical teams.

Lead design and implementation of scalable, fault-tolerant data ingestion systems for the Lakehouse. Build connectors, optimize performance, debug large production clusters, drive architecture and cross-product integration, mentor engineers, and lead technical initiatives.

Design and build systems for service communication across clusters, focusing on API gateways, service discovery, and overload protection.

Own search quality for both AI agents and human users by building hybrid retrieval, ranking models, evaluation frameworks, and relevance guardrails across structured and unstructured data to ensure accurate, high-recall results.

Serve as a technical pre-sales advisor, build client relationships, deliver hands-on Spark and Databricks evaluations, author reference architectures and demos, and advance to an independent Solutions Architect role.

The AI Engineer will develop GenAI applications, oversee production rollouts, advise customers, present at conferences, and collaborate on product roadmaps.