Top AI Specialist Jobs in Seattle, WA

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.

Develop and optimize prompts, context management, and multimodal prompting workflows for LLM-powered products. Collaborate with Customer Success to iterate on prompts, review conversations and feedback, document and teach prompting best practices, and build small prototypes using Python and low-code tools to test complex prompting and data workflows.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead discovery and build AI-enabled operational workflows across R&D and business functions. Translate requirements into practical solutions, own design-to-launch, optimize adoption, and manage Marketing Operations (campaigns, automation, tech stack). Measure outcomes, document solutions, and ensure alignment with shared AI standards.

The SAP AI Specialist will integrate AI within SAP systems, optimizing capabilities using SAP Joule and BTP AI services, and developing predictive analytics and automation solutions.

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.

Lead change management for AI-powered tools and workflows: assess impacts, build adoption plans, create training and communications, coach leaders and enablement teams, recruit change champions, track adoption metrics, and share learnings across the Change Management team.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Sell coding-assistant and AI-native engineering solutions and co-sell NVIDIA developer-platform optimizations. Engage enterprise development leadership, design pilots and benchmarking services, scope consulting engagements, and collaborate within regional PODs to drive AI-accelerated application performance and developer productivity.

Review trainer-submitted image-question pairs and verify golden answers for accuracy and consistency. Flag and document incorrect, ambiguous, or incomplete responses, provide corrective feedback, track recurring errors, and escalate unclear cases. Ensure trainer output meets project quality standards.

Review trainers' completed annotation tasks comparing questions, images, and golden answers to verify correctness. Flag incorrect, ambiguous, or inconsistent responses, provide constructive feedback, track recurring errors, ensure outputs meet quality standards, and escalate unclear cases to the project team.

Perform on-site data annotation and quality assurance for natural language datasets, test AI products, analyze data for consistency and model performance, report anomalies and insights, and collaborate to refine machine learning models.