Top Tech Jobs & Startup Jobs in Seattle, WA

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.

Leads end-to-end Salesforce and full-stack engineering, including frontend experiences, backend services, APIs, data models, integrations, AI-powered automation, testing, deployment, and production support. Uses AI-assisted development tools throughout the SDLC while maintaining code quality, security, and performance. Designs scalable revenue-process solutions, contributes to CI/CD and Agile practices, and elevates engineering standards across the team.

Design and govern large-scale Elasticsearch architectures and migrations. Build high-throughput indexing and semantic vector search (kNN, ANN, ELSER) and RAG pipelines. Optimize performance, capacity, and cluster topology across cloud platforms, influence product roadmap, publish best practices, and mentor engineering teams and enterprise customers.

Provide in-house counsel on product, IP, and marketing matters across product development lifecycle: support patent prosecution and portfolio management, open-source licensing compliance, brand protection, commercial contract drafting for AI/IP, product launch and regulatory governance, legal research and diligence, and backup trade compliance analysis. Collaborate with engineering, product, and external counsel to translate technical concepts into legal strategies.

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.

Lead the technical vision and development of Elasticsearch’s core search infrastructure, including indexing, retrieval, query execution, and relevance. Research advances in search systems and algorithms, guide long-term technical roadmaps, collaborate across teams, mentor expert engineers, and contribute hands-on to high-performance distributed software. Serve as a subject-matter authority while driving projects from concept through completion.

Lead Elasticsearch performance engineering from architecture through production. Develop performance models, optimize distributed systems, profile bottlenecks, build benchmarks, detect regressions, and improve scalability across stateful and serverless architectures. Design AI-assisted optimization and benchmarking tools, collaborate across teams, define performance strategies, and mentor engineers. The role requires deep Java, JVM, concurrency, distributed systems, and search or data-store performance expertise.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Responsibilities include implementing performance models, profiling systems, identifying bottlenecks, building benchmarks and regression detection, improving logging, metrics, vector search, and ES|QL performance, and creating AI-assisted optimization tools. The role also involves architectural and code-level optimization, technical analysis, peer reviews, and guidance for fellow engineers.