Top Tech Jobs & Startup Jobs in Seattle, WA

Build backend APIs, Go services, data pipelines, and agent infrastructure for Vega, LaunchDarkly’s AI-powered observability platform. Design sandboxed agent execution, usage metering, dashboard creation capabilities, and enterprise data integrations. Own features from design through production, operate high-throughput systems, contribute to architecture and code quality, mentor teammates, collaborate cross-functionally, and participate in on-call rotations.

Lead and develop the AgentControl Evaluations engineering team while providing technical leadership for offline evaluations, playgrounds, LLM-as-judges, and annotated datasets. Partner with Product and Design on roadmap planning, own feature delivery, improve reliability and incident response, coordinate shared infrastructure, communicate progress and risks, foster collaborative team norms, and participate in hiring and career development.

Lead and grow a backend/infrastructure engineering team building the Experimentation product. Partner with PM and Design to plan and deliver features, collaborate with adjacent teams on shared infrastructure, improve reliability and observability, drive incident response and operational excellence, and participate in hiring and career development for engineers.

Leads LaunchDarkly’s global partnerships and alliances strategy across GSIs, SIs, cloud, VAR, and technology partners. Builds the partnerships organization, partner programs, co-sell motions, services offerings, and PRM ecosystem. Owns partner-sourced pipeline, influenced revenue, budgets, forecasting, executive relationships, enablement, and cross-functional collaboration across Sales, Product, Services, Marketing, Finance, Legal, and Customer Success.

The Staff Engineer will build data-driven experimentation systems, lead statistical engine design, ensure correctness in A/B testing, and mentor team members while collaborating cross-functionally.

Design, build, and operate scalable backend services and APIs for LaunchDarkly’s experimentation platform. Own systems supporting experiment setup, event ingestion, metric computation, and results processing. Contribute to architecture, reliability, observability, deployment safety, incident response, and technical direction. Collaborate with product, design, data science, and engineering teams, investigate production issues, participate in on-call, and mentor teammates through reviews and knowledge sharing.

Design and build LaunchDarkly’s next-generation experience platform across its product suite. Lead user experience and supporting platform development, collaborate with product teams, mentor engineers, set technical direction, and own operational excellence through monitoring, observability, incident response, telemetry, alerting, and on-call responsibilities.

Own approximately eight strategic enterprise accounts, develop territory and account plans, generate outbound pipeline, and expand customer relationships. Drive LaunchDarkly adoption, manage complex consultative sales cycles, and engage executive stakeholders at Fortune 500 companies. Collaborate with solutions engineering, customer success, support, marketing, product support, developer relations, and revenue operations teams. The role requires experience with large SaaS deals, land-and-expand strategies, quota attainment, and executive-level selling.

Own enterprise feature-management capabilities end to end across Go backend and TypeScript/React frontend. Design for permissions, auditability, scale, performance, APIs, Terraform, data residency, regional isolation, and resilience. Collaborate directly with enterprise customers, improve observability and operability, participate in on-call, align cross-functional teams, mentor engineers, and deliver features from problem framing through production support.

Lead ownership of core feature-flag surfaces to ensure consistent, high-quality UX across teams. Set priorities from customer evidence, drive design-system adoption, prototype hybrid human-agent workflows, improve frontend performance at scale, and build shared interaction primitives (tables, filtering, sorting, bulk changes). Influence cross-team implementation, migrate call sites to shared foundations, and translate platform/library capabilities into product improvements.