Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Serve as a trusted technical advisor for Elastic customers, guiding onboarding, adoption, implementation, consumption, and expansion. Define technical success plans, align Elastic solutions with business objectives, resolve technical friction, coordinate with support and service teams, and identify opportunities to increase customer value and recurring revenue. The role requires hands-on technical expertise, strong communication, customer relationship skills, project coordination, onsite engagement, and frequent travel.

Lead the technical vision, roadmap, and development of Elasticsearch’s ES|QL analytical engine and query capabilities. Design data-intensive systems, algorithms, APIs, and compute infrastructure; research search and analytics technologies; collaborate across product and engineering teams; mentor senior engineers; and contribute hands-on modern Java development. The role requires autonomous technical leadership, expertise in database internals and analytics systems, and the ability to guide complex projects from conception through delivery.

Serves as a trusted technical advisor for Elastic customers, developing technical success plans, guiding onboarding and adoption, resolving technical friction, and increasing solution consumption. Partners with account, solutions architecture, support, and services teams to align Elastic deployments with business goals, improve customer outcomes, identify expansion opportunities, and drive recurring revenue growth.

Drive adoption of Elastic’s AI-powered search and analytics solutions among new and existing state and local government accounts in Texas. Build trusted customer relationships, identify opportunities, develop use cases, navigate complex technology sales cycles, and create territory business plans. The role requires solution selling, public sector sales experience, accurate Salesforce forecasting, and collaboration across business functions. Open source sales experience is preferred.

Set technical direction for Elastic Cloud Serverless control-plane initiatives, designing distributed systems that orchestrate projects across AWS, Google Cloud, and Azure. Lead multi-quarter, cross-team delivery; write and review Go code; improve reliability, security, and cost efficiency; investigate incidents; participate in on-call; mentor engineers; and advise product and engineering leaders on technical trade-offs and roadmap decisions.

Leads competitive intelligence for Elastic Search by analyzing competitors, products, pricing, packaging, marketing, and market trends. Creates battlecards, training, comparisons, blogs, and web content that communicate product differentiation. Tracks competitive developments, supports win/loss analysis, and partners with product marketing, product management, sales, engineering, and leadership to shape positioning and go-to-market strategies. Participates in industry events and translates technical insights into compelling business value.

Lead development of Elasticsearch vector similarity search capabilities, including designing algorithms and data structures, implementing features, fixing bugs, and improving code quality. Collaborate asynchronously with a globally distributed engineering team and open-source community. Serve as a subject-matter expert on vector search relevance and implementation while contributing modern Java code and guiding cross-functional initiatives autonomously.

Lead strategic build-versus-buy engineering initiatives within Elastic’s IT organization. Design and deliver internal platforms using Elasticsearch, Kibana, Elastic ML, AI, and cloud technologies across developer productivity, FinOps, IT service management, and enterprise efficiency. Establish architecture and engineering standards, partner cross-functionally with IT, Security, Platform Engineering, Finance, and other teams, and validate Elastic products through internal production systems.

Designs, deploys, scales, and optimizes enterprise Elasticsearch architectures and high-throughput ingestion pipelines. Leads cluster design, vector and semantic search implementations, performance tuning, migrations, customer engagements, architectural reviews, and technical delivery. Partners with customer and internal engineering teams, provides field feedback, documents implementation practices, and mentors technical staff.

Lead Elasticsearch search relevance and vector search initiatives, designing and implementing new search features, algorithms, data structures, and bug fixes in modern Java. Improve search speed and relevance, contribute to Lucene, collaborate with a globally distributed engineering community, guide projects autonomously, review code, and work with technologies including Elasticsearch, Solr, PostgreSQL, MongoDB, and Cassandra.