Top AI Jobs in Seattle, WA

Lead causal measurement and analytics for media investments: design quasi-experimental and observational approaches, apply interpretable ML and statistics, write reproducible Python/SQL analysis, surface actionable insights for marketing partners, and uphold data ethics and stewardship.

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.

Lead the Applied AI organization, architect AI-focused operating models, manage a team of AI engineers, and redesign business processes for improved efficiency and cost savings.

Sell and shape adoption of CoreWeaves AI Runtime Services by driving technical-commercial strategy, proving value with early customers, creating playbooks, and feeding product roadmap. Advise on serving frameworks, batching, execution isolation, throughput modeling, GPU utilization, and SLA structures while partnering with product, infra, and sales teams.

Lead design and delivery of AI-based systems integrating OpenAI technology across Microsoft. Build, ship, and maintain reliable, observable, and secure software services; collaborate with cross-organizational technical partners; navigate business and technical constraints; write technical briefs; identify and escalate risks to deliver software on schedule.

Lead design and delivery of large-scale AI observability services for Core AI. Own end-to-end development, production readiness, and DevOps practices; collaborate with product, partners, and customers; innovate on reliability, performance, and monitoring for generative AI agent platforms.

Lead development of auction and bidding algorithms for Microsoft Advertising: design and implement bidding strategies and auction mechanisms, run large-scale experiments, build automation and marketplace optimization systems, and develop causal and ML models to improve advertiser ROI and long-term marketplace health.

Design and deliver generative AI and computer vision models and on-device inference for consumer AR experiences. Prototype research advances, optimize models (compression, quantization, distillation), collaborate across teams, and productionize scalable inference pipelines for mobile and wearable platforms.

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.

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.

Lead end-to-end applied AI/ML solutions for payments trust & safety, from problem framing and data strategy through production deployment, monitoring, and iteration. Drive technical direction, evaluation metrics, reproducibility, and compliance-ready documentation while partnering across product, engineering, data, risk, and compliance stakeholders.

Manage delivery of a portfolio of AI and data science projects from planning through implementation. Coordinate technical and non-technical teams, dependencies, requirements, budgets, timelines, and stakeholder expectations. Lead Agile ceremonies, drive accountability, translate AI capabilities into actionable requirements, and proactively identify and mitigate risks across complex, concurrent initiatives.

Build and ship end-to-end GenAI, multimodal LLM, RAG, and multi-agent systems for growth marketing. Design agentic UIs, memory and retrieval architectures, distributed training/inference, behavioral embeddings, observability/safety, and mentor teams while collaborating with product and engineering to deliver production AI products.

Lead AI engineering for Digital Operations: define roadmap, deliver end-to-end AI products (copilots, agents, RAG apps), integrate LLMs and enterprise data, build reusable frameworks, run pilots, ensure production-grade MLOps, governance, and cross-functional adoption.

Serve as the primary technical owner for customer engagements, design and build integrations, write production-quality code, troubleshoot and ship scalable production solutions, capture precise product feedback, and partner with product and engineering to convert field learnings into roadmap improvements.

Develop and test AI/ML software solutions with cross-functional teams. Apply engineering principles, responsible AI practices, machine learning techniques, and software quality standards. Collaborate with stakeholders to define requirements, learn emerging technologies, improve system reliability and performance, and deliver projects in a cooperative environment.

Senior Software Engineer focused on AI infrastructure performance insights and observability. Responsible for designing and building monitoring, instrumentation, metrics, and tooling to measure and optimize compute and platform performance while collaborating with infrastructure and ML teams.

Lead applied research and engineering for feedback-driven agentic AI: define reward modeling and reinforcement learning roadmap, design production learning loops and evaluation frameworks, run large-scale experiments, and ship research into production while partnering across product and engineering.

The Senior AI Engineer will design and build AI-powered automation tools, maintain LLM systems, and collaborate with business analysts to enhance processes across various operations.

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.

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.

Lead development of AI-powered patient experiences: LLM-driven intake and therapist matching, between-session support, evaluation and safety infrastructure, outcome measurement, and HIPAA-compliant product delivery. Partner with Engineering, ML, Data Science, Clinical, and Legal to ship and monitor models in production, write evals, design red-teaming and human-in-the-loop flows, and measure patient outcomes.