Top Tech Jobs & Startup Jobs in Seattle, WA

Build and operate the cloud backbone for an agentic AI platform, including reliable event pipelines, event routing, projections, agent-facing query interfaces, observability, and scalable storage. Own delivery guarantees, replay, idempotency, schema enforcement, dead-letter handling, dashboards, alerting, and feature flags. Collaborate with edge, data, infrastructure, agent, and computer vision teams to support reliable operation at fleet scale.

Lead end-to-end model lifecycle as infrastructure: standardized packaging, model CI/CD, serving with versioned contracts, automated deployment/rollback, monitoring and drift detection. Extend platform discipline to LLM/VLM/agentic workloads (prompt/versioning, generative evaluation, guardrails, token cost/latency observability). Define API boundaries, enable self-serve safe deployments, own operational seams (vector stores, tracing), and mentor engineers to grow the ML/LLM ops function.

Design, scale, and secure cloud infrastructure and platform solutions for a global IoT edge fleet and Agentic AI platform. Own IaC, manage high-availability Kubernetes clusters, drive GitOps deployment automation, enforce zero-trust and secrets management, implement observability and alerting, optimize cloud cost and operations, and produce documentation, runbooks, and architecture artifacts while collaborating across software and hardware teams.

Lead backend architecture and deliver scalable Node.js/TypeScript services and APIs. Optimize CI/CD and deployments (Docker/Kubernetes), improve performance and reliability, mentor engineers, drive engineering standards, and partner with product, QA, and DevOps to translate requirements into robust cloud services.

Lead end-to-end ML data engineering: build and own pipelines that convert raw telemetry and video into versioned, governed training and benchmark datasets. Design schema, storage, dataset versioning, governance, reader/writer libraries, and integrations for researchers; partner with annotation, edge, and MLOps teams and provide technical mentorship.

Lead and grow an engineering team building Agentic AI platforms and distributed edge-to-cloud systems. Drive architecture, AI model operationalization, orchestration, scalability, reliability, MLOps, and cross-functional delivery while hiring, mentoring, and setting technical strategy.

Own end-to-end delivery of a GenAI-powered security deterrence product: design services and APIs, integrate detection models with prompting and voice/TTS, build evaluation and regression suites, ensure precision and safety for real-world actuations, and drive build-vs-buy decisions while collaborating across platform, data, and ML teams.

Lead strategic vision for Intelligence and Ecosystem product management, integrating AI and analytics while ensuring user experience and compliance with security standards.

The Director of Public Sector Capture will lead federal contract acquisition efforts, manage pipeline development, and engage with federal programs to increase winning proposals for AI-driven solutions.

Provide technical leadership for embedded camera platforms, owning system architecture, on-device software, encoding, storage, streaming, and edge analytics. Lead JDM partner integration, cross-functional alignment, mentorship, architecture/code reviews, and adoption of AI-driven development tools to deliver robust edge devices.