Top AI Jobs in Seattle, WA

The Applied Scientist will tackle various machine learning problems, enhance valuation systems, and deploy deep learning models while collaborating with cross-functional teams.

Serve as a global SME for Industrial Metaverse technologies (PLCs, IoT, cloud/edge, digital twins, AI, EMC/RED, cybersecurity). Lead standards work, develop test programs, perform and supervise complex testing, train staff, represent UL externally, and support clients and continuous improvement across regional or global labs.

Architect and scale an internal AI platform and APIs to integrate LLMs into developer workflows. Build autonomous agents, RAG systems, and production-grade tooling to boost developer productivity, ensure reliability, security, and cost-efficiency, and collaborate across product, infrastructure, and security teams.

Design and implement AI agents and Model Context Protocols to integrate enterprise systems (NetSuite, Zuora, Jira) with LLMs. Build secure, SOX-compliant automation and orchestration workflows, measure KPIs, and partner with Finance, IT, and Security to operationalize AI across enterprise applications.

This role involves developing and implementing testing frameworks for ensuring reliability and performance of AI security controls across platforms. The engineer will expand test coverage and contribute to quality metrics for AI models.

The Lead Product Manager will define the product strategy for AI/ML features, collaborating with engineering to deliver innovative solutions, enhancing user experiences, and bridging research with production while making critical decisions in ambiguous situations.

Lead technical direction for cloud platform engineering: design, build, and operate secure, scalable platforms supporting AI/ML and data initiatives. Drive DevEx, CI/CD, DevSecOps, observability, self-service developer workflows, and AI-assisted development including agent and MCP integrations.

Design, build, and operate production-grade AI tools, automations, and integrations for HR workflows. Lead LLM-based solutions (prompting, RAG), integrate people systems (Workday, Slack, Google Suite), improve data quality, support end users, and drive measurable productivity and product roadmap decisions.

Design and build AI agents, first-party web and mobile apps, and scalable backend services. Integrate LLM frameworks and enterprise systems, implement APIs and microservices, ensure observability and security, and collaborate with Finance, Security, and Engineering stakeholders.

Build and deploy agentic and generative AI copilot and autopilot systems for Risk and Compliance. Own end-to-end systems (data, API integrations, prompt tuning, orchestration, monitoring). Leverage payment, blockchain, graph, and unstructured data to train transformer-based models. Collaborate cross-functionally to productionize and monitor ML at scale, driving strategic roadmaps and significant business impact.

The Director leads the Social Intelligence Analytics team, advising clients, managing projects, and utilizing AI to derive insights from social media data.

The Young Investigator in Robotics will focus on developing and applying AI methods in robotics, including manipulation, skill learning, and sim-to-real transfer while individually pursuing independent research.

Design, test, and validate scalable readout circuitry for topological qubits; codesign readout with qubit and control teams; analyze and present measurement results; build tools and processes to accelerate quantum research; document work, uphold safety protocols, and collaborate across interdisciplinary teams.

Serve as a strategic technical partner for key customers: design and advise on cloud architectures, run technical workshops, proactively monitor usage, resolve escalations with engineering, drive retention and expansion, and develop tools and documentation to improve Technical Account Management efficiency.

Lead Grow's AI Enablement team to define and execute the company-wide AI roadmap. Build and operate core AI infrastructure (data pipelines, embeddings, retrieval, model access, connectors, and governance) with PHI compliance. Architect integrations and APIs enabling agentic workflows, drive delivery of high-priority LLM and AI-assisted care use cases, and manage vendor governance, procurement, and cross-functional alignment.

Design and implement scalable platform services, runtimes, and developer tooling for deploying and managing AI workloads on Arm-based edge devices. Build abstractions, observability, and performance optimizations across heterogeneous hardware while collaborating with architects and AI engineers to produce robust, maintainable systems and SDKs for on-device AI.

Lead AI partnership strategy and execution to grow AI Frontier Labs alliances. Own alliance performance, co-sell pipeline, joint GTM and solution development, partner account mapping, enablement, marketing, and executive alignment to scale generative AI adoption and revenue.

As a Staff Product Manager, you'll drive the strategy and success of SIEM products, collaborating with various teams to fulfill customer needs and market demands while focusing on security for SMBs.

Build and operate core AI observability services: design, implement, and deliver large-scale cloud services; own development lifecycle and production readiness; collaborate with product and stakeholders; drive DevOps culture; engage customers and improve availability, reliability, performance, and observability of AI agent products.

Design and prototype AI-native, agentic user experiences by delivering coded prototypes (React/TypeScript), leveraging LLMs and generative tools, and partnering with product and engineering to ship scalable, data-driven AI features and design system primitives across the platform.

Lead architecture, design, and delivery of large-scale GenAI-enabled, distributed systems. Manage and mentor engineering teams, define standards and APIs, integrate LLMs and agentic workflows, ensure production readiness, observability, scalability, and partner cross-functionally with Product, AI/ML, Data Engineering, and DevOps.

Lead ZAIDYN's AI Engineering function to design, build, and ship an enterprise-grade agentic AI platform. Own architecture, integrations (AWS Bedrock/AgentCore), LLMOps/eval frameworks, observability, governance, and team hiring/operations. Ensure production readiness, cost/latency controls, auditability, and cross-functional delivery with product and QA while representing the platform externally.

Lead org-wide developer experience and AI-enabled developer workflows. Identify and solve high-leverage bottlenecks across build systems, monorepo tooling, CI/CD, and test reliability. Drive standards, enable monolith-to-modular migration, embed with product teams, mentor engineers, and deliver AI-native developer tooling and adoption at scale.

Support internal audits across financial, operational, and technology areas. Evaluate controls and SOX testing, analyze large datasets to identify risks, develop automated testing/continuous monitoring, and advise process owners on improvements while building audit, analytics, and risk-management skills.

Build and deliver AI-native, agentic systems for healthcare customers end-to-end: discover customer needs, architect and code solutions, manage onboarding and production reliability, mentor newer builders, and ensure compliance with federal and healthcare data protections.