Top Tech Jobs & Startup Jobs in Los Angeles, CA

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 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.

The role involves leading initiatives for vector search in Elasticsearch, enhancing features, resolving bugs, and contributing to community engagements in a distributed team setting. A strong background in vector similarity and Java is crucial.

Develop and scale account-based marketing programs across priority Americas accounts. Partner with sales, customer success, and marketing teams to create personalized multichannel campaigns targeting technical and executive buyers. Manage campaign strategy, messaging, paid media, events, budgets, and timelines while measuring account engagement, pipeline influence, velocity, and ROI. Use performance insights to optimize programs and evolve ABM playbooks for enterprise technology audiences.

Own and scale account-based marketing programs for priority public sector accounts across AMER. Develop personalized, multichannel campaigns targeting government decision-makers, manage budgets and timelines, coordinate events and agencies, build landing pages and messaging, and measure account engagement, pipeline influence, velocity, and ROI. Partner with sales, customer success, product marketing, content, and regional teams while navigating government procurement, compliance, and buying cycles.

Design, build, test, deploy, and support full-stack Salesforce and integration solutions. Develop frontend components, backend services, APIs, data models, REST and event-driven integrations, and AI-powered automations. Use Salesforce technologies including LWC, Apex, SOQL/SOSL, and Flows. Apply AI-assisted development throughout the SDLC while maintaining code quality, security, and performance. Contribute to CI/CD, automated testing, code reviews, Agile ceremonies, architecture, debugging, and cross-functional technical collaboration.

Drive new business and account expansion within enterprise and strategic accounts of more than 4,000 employees. Build demand for Elastic’s search, security, observability, and cloud solutions; engage developers and executives; identify use cases; manage complex sales cycles; close transactions; forecast accurately in Salesforce; and develop account growth plans through customer, partner, and community ecosystems.

Own product roadmap and vision for Elastic Cloud Control Plane. Prioritize orchestration, scaling, and management capabilities; collaborate with engineering, sales, and marketing; gather market and customer insights; drive cross-functional execution and go-to-market activities.

Design, implement, and maintain Okta identity and access management solutions, integrating Okta with cloud/SaaS applications. Build SSO and MFA deployments, automate provisioning using Workflows/SCIM/JIT, and create automation via REST APIs and webhooks. Perform audits, monitor identities and access, troubleshoot integrations, and collaborate cross-functionally to meet business requirements.

Lead Elastic’s strategy, vision, and multi-quarter roadmap for vector databases, embedding and reranking models, vector indexing, semantic ingestion, and search capabilities. Conduct market and competitive research, define product metrics, prioritize features, and partner closely with engineering, cloud, and applied research teams. Guide technical trade-offs involving recall, latency, index size, ingestion throughput, model lifecycle, and total cost of ownership across serverless and self-managed deployments.