Top Tech Jobs & Startup Jobs in Los Angeles, CA

Leads order-to-revenue compliance for usage-based revenue, overseeing metering, billing controls, product launches, partner royalty reconciliations, SOX compliance, audits, technical accounting, and issue remediation. Manages functional leads and partners with Engineering, Finance Data Systems, Sales Operations, FP&A, executives, and auditors to validate monetization processes, resolve metering issues, and ensure accurate revenue conversion.

Build and productionize customer-facing data and AI solutions on the Databricks Platform. Own architecture, design, implementation, deployment, and integration of data pipelines, distributed systems, ML/AI models, and applications. Lead technical delivery, advise enterprise stakeholders, train customers, resolve implementation issues, and contribute reusable frameworks and product feedback. This role requires customer immersion, cross-functional collaboration, and travel to customers approximately 20% of the time.

Build and productionize customer data and AI solutions on the Databricks Platform. Own architecture, design, development, deployment, and integration of scalable data pipelines, ML/AI models, and applications. Collaborate with customers, engineering, product, and project teams; provide technical guidance, training, documentation, and implementation support. Deliver measurable project outcomes, resolve technical issues, create reusable accelerators, and influence product direction. Travel to customers approximately 20% of the time.

Lead technical strategy for customer accounts, design scalable data engineering and real-time analytics architectures, and drive Databricks adoption. Advise senior customer stakeholders, lead architecture discussions, develop custom solutions for competitive opportunities, coordinate cross-functional teams, and influence product direction. The role requires deep expertise in Spark, Kafka, data warehousing, cloud platforms, Python, SQL, distributed systems, and production deployments. Travel may reach 30%.

Design and deploy production ML/AI architectures on the Databricks platform, lead Generative AI (LLM, RAG, agent) implementations, optimize and scale MLOps pipelines, provide technical pre-sales support, and translate customer feedback into product improvements while mentoring peers and meeting delivery milestones.

Advise enterprise customers on designing, securing, administering, and deploying Databricks environments on Microsoft Azure. Architect scalable cloud infrastructure, networking, identity, disaster recovery, observability, and infrastructure-as-code solutions. Support pre-sales activities through proof-of-concept architectures and technical content, while sharing expertise through training, tutorials, hackathons, conferences, and open-source contributions.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the vision, strategy, and roadmap for Databricks’ AI-first learning platform. Build contextual guidance, adaptive learning paths, learner models, assessments, skills graphs, analytics, and personalization tools. Partner with engineering, UX, curriculum, education, and go-to-market teams to deliver scalable learning experiences for customers, partners, and employees. Define metrics, understand skills gaps, engage users, and improve platform adoption through embedded learning capabilities.

Lead technical strategy for customer accounts by designing scalable data, AI, streaming, and analytics architectures on Databricks. Advise senior technical stakeholders, drive platform adoption and consumption growth, conduct architecture discussions, build competitive solutions, coordinate cross-functional resources, and provide product feedback. The role requires strong Python and SQL coding, public-cloud deployment experience, distributed data systems expertise, and excellent technical communication.

Leads and scales a customer-facing AI Forward Deployed Engineering team, overseeing hiring, mentoring, strategic AI initiatives, enterprise engagements, and production AI delivery. Builds executive customer relationships, partners with Sales, Product, Engineering, and GTM, influences product strategy through customer insights, manages account and services outcomes, and represents Databricks as an AI thought leader.