Top AI Automation Jobs in Seattle, WA

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 architecture, development, deployment, and operation of scalable AI services and observability platforms. Drive technical strategy, reliability, security, performance, automation, and operational excellence. Partner with product and engineering teams, engage customers, resolve complex issues, make architecture decisions, manage dependencies, mentor engineers, and promote high-quality engineering practices across testing, privacy, compliance, and code quality.

Design, build, and operate production AI automations and agentic workflows for Toast’s customer care systems. Integrate LLMs with Salesforce Service Cloud, Amazon Connect, and workflow platforms; develop autonomous actions with human oversight; test, monitor, and improve system reliability, accuracy, latency, and cost. Collaborate with software engineers, Salesforce developers, and care operations stakeholders to translate workflows into scalable intelligent solutions.

The AI Deployment Engineer will build, deploy, and scale AI solutions while collaborating across departments to ensure successful implementation and support of operational workflows.

Leads company-wide AI adoption, operating the AI Center of Excellence, developing champions, running cross-functional AI sprints, delivering training, managing AI tools and budgets, and measuring workflow adoption, time savings, and financial impact. The role partners with Engineering to distribute shared AI skills, evaluates vendors, reports outcomes to executives, and publishes successful use cases across departments.

Architect and build production agentic AI systems for customer support and compliance automation. Lead technical direction for distributed systems, APIs, orchestration frameworks, guardrails, and evaluation systems. Create reusable automation primitives, improve grounding and reliability, reduce hallucinations, and mentor engineers on LLM application design and production readiness. Collaborate cross-functionally to scale AI automation across Coinbase.

Lead the business-side AI Operations function to translate enterprise AI capabilities into operational implementation, adoption, training, hypercare, and sustainment. Build operating models, readiness frameworks, change plans, KPI tracking, and team capabilities to scale AI across the organization and ensure initiatives move from pilots to measurable business outcomes.

Leads enterprise AI transformation by developing the AI roadmap, prioritizing investments, managing initiative portfolios, and delivering measurable business value. Partners with executives and cross-functional teams to redesign operations, establish governance, evaluate technologies and vendors, drive adoption, and lead workforce change. Accountabilities include revenue growth, productivity, efficiency, customer experience, compliance, AI maturity, and value realization.

Hands-on technical leader who designs, builds, and deploys production-grade AI automation and agentic workflows. Responsibilities include rapid prototyping, RAG and document-intelligence systems, API integrations, orchestration, monitoring, reusable AI assets, and mentoring a small engineering team to deliver frequent releases and measurable business impact.

Build and deploy production micro-apps and LLM-powered agents on a governed GCP platform. Integrate AI with systems (Salesforce, Slack, NetSuite, SQL), harden apps with auth, secrets, CI/CD, logging and monitoring, automate maintenance, and implement evaluation and observability for model quality and drift.

Lead the business-side AI Operations function to translate enterprise AI into adopted, measurable, and sustainable business practices. Build operating models, readiness frameworks, launch and hypercare plans, sustainment processes, and team capabilities. Partner with IT, AI Innovation, product, and business stakeholders to drive adoption, change management, KPI tracking, and continuous improvement across the organization.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Support AI project teams by executing workstreams, preparing client-facing presentations and documentation, assisting implementation activities, maintaining required certifications, using relevant technology, communicating with stakeholders, and traveling as needed for client engagements.

Works with the CFO organization to analyze finance workflows, identify opportunities to eliminate or automate work, and prototype AI and agentic technology solutions. Responsibilities include interviewing employees, documenting processes, researching technologies, building proofs of concept, testing solutions, gathering feedback, measuring results, and documenting recommendations. The intern collaborates with finance leaders and internal or external partners to redesign operating processes.

Lead Net at Work’s transformation into an AI-native company by redesigning workflows, deploying virtual workers, building AI capabilities, training employees, and managing adoption. Establish the internal AI tool stack, standards, and use-case pipeline while delivering measurable operating leverage through reduced cycle times, improved quality, increased capacity, and margin gains. Validate results with Finance and drive organization-wide change through influence, process redesign, and strong stakeholder leadership.

Leads and grows a client-facing AI and data services practice, owning strategy, offerings, delivery methods, team development, client outcomes, sales support, and P&L performance. Guides clients from data readiness and AI use-case discovery through production deployment, adoption, and measurable business results. Advises executives, scopes complex engagements, builds delivery teams, and develops managed, subscription, and advisory services.

Lead client engagements in insurance data, analytics, and AI: define roadmaps, run discovery sessions, design solutions, manage delivery and teams, develop proposals, and ensure DataOps, cloud (AWS), governance, and best practices across AI and analytics initiatives.

Develop and maintain software, test automation, and Azure Machine Learning pipelines for embodied AI and robotics research. Responsibilities include preparing robotic datasets, integrating simulation environments and physical robotic platforms, deploying and evaluating novel algorithms, managing model fine-tuning workflows, troubleshooting production systems, and supporting unit testing and documentation.

Enable and mentor partners to sell and deliver NiCE AI/CCaaS solutions. Lead technical discovery, demos, PoVs, and architecture reviews; build partner enablement content; manage technical partner relationships, integrations, release impacts, and service scoping.

The Principal Consultant leads AI and digital transformation engagements, guides clients in identifying AI opportunities, builds strategies and roadmaps, implements solutions, and develops teams to achieve measurable business outcomes.

Own and administer Salesforce and NetSuite while designing and deploying production-grade AI-driven automations and agent workflows. Ensure data governance, PHI/HIPAA compliance, release management, and quote-to-cash integrity. Partner cross-functionally to prioritize work, coach teams, document systems, and measure impact of automation on operations and revenue.

Lead AI-driven reconciliation and automation to improve encounter data quality. Own model performance, identify root causes, partner with technical and business teams to enhance models, prioritize roadmap, and scale automation while communicating results to stakeholders.

Build and ship AI-native systems for a fintech app: AI agents, RAG/retrieval systems, tool-calling and automation for onboarding, KYC, support, risk, CRM and operations. Work with product and engineering to design reliable, low-hallucination, cost- and latency-aware solutions and turn manual processes into scalable AI-enabled systems.

Develop AI capabilities using Microsoft tools, integrate AI solutions within enterprise systems, ensure compliance and security, and collaborate with team members for continuous improvement.

Lead data science strategy and a rapid-prototyping team to build production-grade ML and GenAI solutions for contractor earnings, tax, and compliance. Drive model governance, automation, and cross-functional delivery to reduce errors, mitigate risk, and scale measurable ROI across product, engineering, and operations.