Top AI Automation Jobs in Seattle, WA

Build and maintain internal and customer-facing web/cloud apps and AI automations. Integrate with third-party APIs (QuickBooks, Microsoft Graph, Zoho, Zoom), implement generative-AI features, ensure security, deploy to cloud, and collaborate with leadership and IT. Work independently on design, testing, and maintenance across varied projects.

Design, build, and deploy production agentic AI systems for internal operations and client-facing services. Own AI architecture, agent orchestration, integrations, deployment pipelines, governance, monitoring, and continuous improvement. Develop productized AI offerings, evaluate emerging platforms and LLMs, define KPIs, and connect deployments to measurable business outcomes. Collaborate with executive and engineering teams while establishing the foundation for a scalable AI practice.

Lead development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

Lead enterprise adoption of Microsoft Copilot, Copilot Studio, and Power Platform by analyzing business processes, designing AI agents, building ROI-backed automation roadmaps, delivering training and prompt engineering best practices, and measuring utilization and productivity improvements across functions.

Design and execute test strategies and automation for cloud-native and GenAI/AI-ML systems. Perform functional, integration, performance, security, and API testing; validate model accuracy, fairness, robustness, and data quality; integrate automation into CI/CD; track defects; mentor junior QA engineers.

Build AI-powered workflows, agents, and integrations to automate marketing research, creative asset preparation, campaign analysis, reporting, and internal coordination. Prototype and productionize LLM-based tools, connect data sources and ad platforms, validate automation quality with real use cases, and document systems for reuse and scaling.

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.

Build and ship AI-driven automation across the go-to-market lifecycle: prospecting, lead routing, deal support, retention, and instrumentation. Design agents and workflows, connect GTM systems and data, deploy and monitor production AI, set guardrails and evals, and partner with Sales, Solutions Architecture, Marketing, and RevOps to measure and improve impact.

Design, develop, and deploy generative AI models and AI-driven automation workflows. Integrate models via APIs, build inference pipelines, preprocess and manage training data, ensure data privacy, monitor and optimize model performance, collaborate with cross-functional teams, and document solutions.

Design and build automation frameworks and evaluation pipelines for agentic AI products. Develop non-deterministic tests, golden datasets, tool-use validation, prompt regression tests, latency/token monitoring, hallucination detection, and collaborate with AI engineers to convert requirements into measurable automated test cases.

Lead QA Automation for agentic AI products by designing eval pipelines, golden datasets, and automated tests for tool-use, hallucination detection, latency/token monitoring, and regression across models and prompts. Integrate performance testing into CI/CD and collaborate with AI engineers to convert requirements into measurable automated evaluations.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

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.

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.

The AI Automation Engineer will apply AI in finance operations to automate processes like AP, AR, and reconciliation, ensuring compliance and performance measurement.

Build and maintain integrations and automations connecting CRM, Microsoft 365, e-signature, custodial/banking systems and reporting. Use LLMs (Claude) and automation tools to extract, process, and verify document-heavy workflows with human-in-the-loop review, monitoring, and auditability, within security and compliance frameworks. Partner across teams and help set AI/automation standards.

Lead the design and implementation of AI agents and automation across pro-code and no-code platforms. Define repeatable automation patterns, integrate AI platforms with business tools via APIs, build RAG pipelines and vector DB integrations, write Python scripts for complex integrations, and guide technical decisions while working closely with the VP of AI to review agent performance and scale solutions.

The Director of AI Automation leads AI-driven automation systems, translating strategic goals into practical solutions, managing teams, and enhancing operational efficiency.

Join a talent pool to teach, author, or advise on AI-powered automation. Deliver live workshops, create course materials, design exercises, shape curriculum, review technical content, and support program updates. Part-time (10–15 hrs/week), remote with collaboration in European time zones. Roles span junior to senior levels and emphasize hands-on experience with automation platforms and real-world operational workflows.

Build and own an internal AI-powered recruiting pipeline: end-to-end LLM-based sourcing, screening, AI interviews, evaluation logic, and deep integrations with ATS and scheduling to automate hiring workflows.

The AI Automation Engineer develops AI-driven systems to automate sales and marketing workflows, partnering with various teams to enhance revenue generation and process efficiency.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Design and deliver AI-powered analytics, dashboards, and decision-support tools for commercial healthcare teams. Build LLM-based agents, use cloud data platforms (Azure/AWS/Snowflake), ensure data governance and compliance, translate complex healthcare data into executive-ready insights, and automate insight generation to support growth and operations.

Pre-sales technical architect advising on Microsoft Copilot and Power Platform adoption. Engage executives, run workshops, design and deploy custom Copilot agents, build prototypes and integrations, and develop automation using Power Automate/Power Apps/Power BI while guiding change management and governance.