Top AI Jobs in Seattle, WA

Lead the AI engineering roadmap for Digital Operations, delivering end-to-end AI products (LLMs, RAG, copilots, agents) from prototype to production. Integrate AI with enterprise data, marketing systems, and cloud platforms, build reusable frameworks, ensure governance and monitoring, and drive adoption through pilots and measurable business impact.

The VP of Product will lead CoreWeave's Research Training Stack, focusing on enhancing AI infrastructure, ensuring quality for pre-trained models, and connecting researchers with advanced cloud capabilities.

Build end-to-end agentic AI systems for healthcare customers: discover needs, architect and code solutions, onboard customers, monitor and iterate production systems, mentor junior builders, and collaborate with stakeholders to deliver reliable, AI-native patient workflows.

Develop and run rigorous benchmarks and profiles for LLM inference workloads to identify bottlenecks and drive targeted performance optimizations across frameworks, runtimes, and GPU hardware. Design experiments (quantization, caching, speculative decoding), validate changes against real traces, partner with platform engineers to productionize improvements, and produce clear technical writeups to guide model-serving, runtime, and hardware decisions.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead product management activities for commercial and internal software products across the lifecycle. Support large enterprise software implementations and program delivery, maintain program controls, report on risks and finances, mentor junior staff, manage stakeholder relationships, and align project objectives with strategic goals while driving continuous improvement.

Use AI coding agents to build end-to-end applications, automations, and basic agents. Translate customer needs into deployed solutions, instrument and iterate on outcomes, evaluate AI output for security/privacy/quality, engage with customers, and document prompts and patterns.

Lead end-to-end product builds by orchestrating AI coding agents to create applications, automations, and basic agents. Translate customer problems into deployable solutions, instrument usage and outcomes, evaluate AI output for security/privacy/quality, engage with customers to find automation opportunities, and document prompts, patterns, and approaches for the team.

Use AI coding agents to build end-to-end applications, automations, and basic agents. Translate customer needs into deployed solutions, instrument and iterate on outcomes, evaluate AI output for security/privacy/quality, engage with customers, and document prompts and patterns for the team.

This role involves developing and maintaining CI/CD pipelines, enhancing deployment processes, ensuring infrastructure reliability, and promoting best practices within the AIDR platform team.

Lead technical direction and architecture for DAP Repository Flows, design and ship autonomous and scheduled agents that operate on customer repositories, improve DAP onboarding, collaborate across teams on platform interfaces, mentor engineers, and solve high-scale technical problems to raise engineering quality.

Lead design, build, and deploy of large-scale data platforms for LLMs, RAG, and agentic AI systems. Hands-on coding, architecting fault-tolerant pipelines, establishing MLOps/DataOps best practices, mentoring engineers, and operationalizing research into production across Exabyte-scale distributed systems.

Lead the Registry design org end-to-end: set UX vision, KPIs, and quality standards; ship cross-platform web and mobile experiences; embed AI-native workflows; prototype and contribute production-quality interfaces; run generative and evaluative research; scale design systems; partner with PMs, engineers, and analytics; and hire, develop, and manage a high-performing team of product designers.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

As a Staff AI Engineer, you'll lead AI product development, overseeing technical direction, system deployment, and model evaluation while collaborating across teams.

The role involves designing AI systems for mental healthcare, focusing on building scalable, production-grade systems that enhance patient engagement and clinical operations. Responsibilities include setting technical standards and ensuring safety and reliability while working with advanced AI technologies.

Own and improve the AI Social render pipeline and agent loops that generate on-brand Instagram carousels and reels. Build prompts, structured outputs, tool-calling, and media composition to ship high-quality generative image, video, voice, and music products in collaboration with product, design, and content strategy.

Lead cross-functional programs to transform customer support with AI-powered automation, agent tooling, analytics, and vendor evaluations. Define roadmap, size opportunities, set success metrics/OKRs, manage dependencies, and drive rollout/change management while partnering with Product, Engineering, Analytics, and Operations to deliver measurable CX improvements.

The Predoctoral Young Investigator role involves developing robots, exploring foundational models, and contributing to open-source research, tailored for early-career candidates aiming for PhD programs.

Lead privacy governance for Microsoft Finance by advising stakeholders, driving compliance with privacy standards and regulations, improving processes through standardization and automation, managing privacy incidents, conducting Privacy Reviews and DPIAs, and measuring program effectiveness across global teams.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

Manage, coach, and develop a team of 10–12 BDRs to hit activity, pipeline, and quota targets. Build and standardize BDR motions with Marketing and Sales, own hiring/onboarding/ramp, report performance, and partner cross-functionally to translate field insights into campaigns. Drive data-informed coaching and performance management to generate pipeline and revenue.

As a Knowledge Development Engineer, you'll architect and deploy AI-driven production systems, reverse-engineer existing systems, and guide product development. You'll synthesize customer feedback and lead experiments to connect technical development with business outcomes.

The Knowledge Development Engineer leverages AI agents to solve customer problems by building applications and automating workflows, focusing on delivery speed and quality.

Lead development of a Semantic Brain: map raw event logs to industry ontologies, build concept/identity-anchored graphs, design reward extraction and off-policy evaluation, deploy agentic LLM orchestration and scalable data pipelines to enable autonomous enterprise decisioning.