Top AI Automation Jobs in Seattle, WA

Design, develop, and deliver large-scale AI services, cloud platforms, and distributed systems for enterprise agent applications. Build observability, evaluation, optimization, automation, and deployment-safety capabilities across AI lifecycles. Improve tooling for fine-tuning and research workflows, optimize model-data-infrastructure interactions, and ensure reliability, security, scalability, and operational excellence. Collaborate with CoreAI and Azure partner teams through design, implementation, code reviews, and production delivery.

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.

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.

Leads AI engineering strategy, team development, and delivery of scalable AI and machine learning solutions. Provides technical guidance on solution design, MLOps, automation, DevSecOps, testing, and operational readiness. Partners with business, data, security, architecture, and technology stakeholders to translate requirements into secure, reliable capabilities. Oversees delivery risks, dependencies, quality, governance, responsible AI practices, and continuous improvement while communicating progress and outcomes to leadership.

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.

Design, build, and operate AI-powered automation, CI/CD systems, distributed services, developer tooling, and code-intelligence platforms. Own significant capabilities from architecture through production, improve engineering workflows using measurable evaluations, scale reliable automation and delivery systems, and operate secure multitenant services. Lead technical reviews, define reliability practices, integrate platforms through APIs and MCP, mentor engineers, and drive ambiguous technical problems to dependable production outcomes.

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.

Build and maintain AI agents, automations, data systems, landing pages, dashboards, and workflow integrations for dealership marketing, sales, finance, and service teams. The role requires unifying data from CRM, DMS, websites, and advertising platforms; automating lead and customer workflows; evaluating AI tools; and documenting scalable solutions. This is a fully remote, independent role with opportunities to grow into senior or lead responsibilities.

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.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Build and productionize AI agents and intelligent workflows using LLMs, RAG, tool use, enterprise data, and workflow orchestration. Identify high-value automation opportunities, develop secure and observable integrations, uncover operational patterns, and deliver measurable improvements in efficiency, quality, self-service, and customer experience. Initially focused on Sales Support, the role will scale successful AI capabilities across the broader Commercial organization.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Build and operate AI-powered automation, CI/CD systems, distributed services, developer tools, validation platforms, and code-intelligence capabilities. Own significant systems from architecture through production, improve engineering workflows using measurable results, scale reliable automation and delivery platforms, and integrate capabilities through APIs and MCP. Establish operational practices, participate in on-call support, conduct technical reviews, mentor engineers, and lead cross-team delivery of dependable engineering platforms.

Intern will identify productivity challenges and process gaps across global sales teams, prioritize improvement opportunities, and build AI-enabled solutions using Microsoft Copilot, agents, chatbots, Excel automation, and related tools. The role also supports sales process documentation, implementation planning, stakeholder collaboration, governance, and measuring efficiency improvements and business impact.

Build and deploy AI agent systems that automate complex business processes. Analyze workflows, design and configure agents, integrate AI with enterprise applications, develop connectors and APIs, and establish evaluation and monitoring systems. The role requires expertise in cloud AI services, LLMs, NLP, Python, integration platforms, conversational AI, RAG, vector databases, APIs, and SQL/NoSQL systems. The engineer will also explore emerging AI technologies and mentor junior developers and system administrators.

Lead design and delivery of agentic AI systems and LLMOps on AWS to generate, validate, and deploy infrastructure-as-code (Terraform). Build multi-agent applications, RAG pipelines, and AIOps for cloud operations; integrate AI into CI/CD and ITSM. Set technical direction, establish guardrails/policy-as-code, curate reusable Terraform modules, and mentor engineering teams.

Leads AI presales strategy, customer advisory, technical solution architecture, and team development. Translates business needs into AI use cases, prototypes, business cases, roadmaps, and repeatable offerings. Partners with sales, engineering, consultants, and technology vendors to support complex pursuits, executive briefings, demonstrations, proofs of concept, and AI business growth. Promotes responsible AI governance, tracks pipeline performance, develops thought leadership, and remains hands-on in high-impact customer engagements.

Build AI-powered software automating hiring, finance, capital planning, contract analysis, and operational workflows. Develop production features using LLM APIs, MCP servers, and agentic frameworks; integrate enterprise systems; transform expert processes into structured data and generated work; and collaborate directly with finance, legal, recruiting, accounting, and delivery teams. The role emphasizes autonomy, rapid execution, product judgment, and forward deployment with business experts.

Identifies business opportunities for AI and automation, gathers and documents requirements, develops business cases, supports solution design and delivery, facilitates stakeholder collaboration, assists with testing and change management, and tracks project outcomes, reporting, and benefits realization.

Leads AI enablement and solution delivery across Finance, including identifying use cases, training employees, designing AI-enabled workflows, integrating ERP and finance systems, and managing data readiness, governance, controls, and audit compliance. Builds solutions for FP&A, close, revenue, audit, and procurement while measuring efficiency, automation, forecast accuracy, and reduced manual effort. Partners with Technology, Data, and enterprise AI stakeholders to align strategy and implementation.

Leads enterprise AI and intelligent automation strategy, including Generative AI, machine learning, and RPA initiatives. Manages a multidisciplinary IT team, budgets, vendors, governance, project portfolios, and end-to-end solution delivery. Partners with business and technology leaders to identify automation opportunities, develop business cases, ensure compliance and security, and deliver scalable solutions with measurable business value. The role is hybrid in Camden, New Jersey, with 15% domestic and international travel.

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.

Build and scale agentic AI systems that automate customer experience workflows across Slack and Salesforce. Analyze transcripts, detect SLA risks and escalations, provide self-service operational insights, and develop AI memory architecture. Partner with data, QA, workforce management, and customer advocacy teams to ensure system accuracy, reliability, trustworthy outputs, and measurable operational impact. Productize internal tools and design human escalation patterns for scalable deployment.

Build and operate an AI-driven global sourcing platform covering web crawling, data ingestion, normalization, entity resolution, product matching, provenance, and source monitoring. Integrate Zoho CRM and QuickBooks, apply LLMs with structured evaluation and human review, and identify automation opportunities across business departments. Lead pilots, train employees, measure impact, and scale the platform to hundreds of sources.