Top Tech Jobs & Startup Jobs

Lead and scale a Forward Deployed Engineering team for Public Sector customers, overseeing technical delivery of large-scale data migrations, AI/ML and GenAI programs. Partner with sales and product teams to scope and deliver professional services, enforce delivery quality and risk management, mentor engineers, and act as escalation point for high-stakes customer situations.

Lead strategy and roadmap for Databricks' SAP platform, build AI-driven agentic automation on top of SAP, own ingestion and modeling of SAP data into the Lakehouse, act as product owner through delivery, and align Finance, Procurement, and engineering to drive adoption and measurable automation outcomes.

Lead technical direction for Databricks Access Management: evolve the core authorization service, unify permission-checking across the platform, build fine-grained access controls (scoped service identities, delegated access, RBAC), implement network ingress access policy, and improve availability and reliability of a low-latency, high-throughput authorization service.

Run and own AI-first sales development programs: design metrics, reporting, governance, adoption, and sequence management. Drive executive cadences, prioritize with sales leaders, build data foundations and field-facing reporting, and partner across AI Ops, Sales Ops, GTM Analytics, and Enablement to scale AI-native prospecting.

Lead and scale Databricks' global web marketing function: build a product-focused team, modernize web properties for humans and AI agents, implement personalization and testing, apply AI to automate web workflows, ensure machine-readable content and strong information architecture, drive analytics-informed growth, manage vendors, and coordinate global marketing efforts.

Build and improve backend AI infrastructure powering model training, serving, and developer-facing AI products. Improve reliability, latency, and efficiency of distributed AI workloads, collaborate with platform and ML teams, and ship scalable APIs and deployment workflows for Databricks AI services.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

Develop pipeline and territory strategy, engage prospects via inbound/outbound outreach, identify Databricks use cases to grow consumption, and support the sales team through technical solution selling and strong customer-centric communication.

Lead technical relationships with major AI labs to define joint roadmaps, design and build platform-to-platform integrations, create POCs and reference architectures, enable strategic customers, and produce field enablement content. Act as hands-on technical owner across product, engineering, partnerships, and GTM to drive joint AI solutions.

Lead the development of the Workspace Platform infrastructure and manage software engineering teams to enhance user experiences across Databricks products.