Top Tech Jobs & Startup Jobs in Seattle, WA

Lead and architect scalable agentic AI runtime services integrating LLM-based reasoning. Manage and mentor a distributed team, drive technical roadmap, deploy models in microservice environments, and collaborate cross-functionally to deliver production conversational AI solutions.

Design and implement a scalable AI Services Platform: context intelligence, agent orchestration, RAG pipelines, distributed multi-region orchestration, observability and safety systems, and evaluation frameworks. Collaborate with product and infra teams to define APIs and integrations, and keep platform capabilities current with LLM and vector DB advances.

Lead product strategy and roadmap for AI-powered search, driving semantic, multi-modal, and personalized search experiences. Partner with engineering and data science to design ranking models, optimize relevance metrics, and integrate search across platforms to improve discovery, performance, and user engagement.

Design and optimize GenAI solutions, collaborate with teams, enhance system performance, present technical findings, and stay updated on GenAI advancements.

Contribute to AI research in LLM post-training and reinforcement learning, developing scalable systems for Zoom's AI Companion. Engage in innovative research, implement model architectures, and partner with teams to translate prototypes into production systems.

The AI Infrastructure Engineer will develop and optimize infrastructure for training large language models, focusing on distributed systems and GPU programming.

Provide on-site IT support for Seattle office staff and executives: troubleshoot hardware, software, networking, and SaaS; manage device lifecycle, onboarding/offboarding, identity provisioning, endpoint management, and documentation; maintain SLAs and CSAT while coordinating with Asset Management, Procurement, and Workplace teams.

Design and implement backend orchestration for agent workflows and runtime in microservices. Build scalable LLM-powered systems (RAG, tool-use, multi-step reasoning), integrate LLM/TTS/ASR, develop agents with frameworks like LangChain/Dify/OpenAI SDK, optimize prompts, run integration tests, and collaborate with research and product teams to deploy agentic AI across verticals.

Build and deploy end-to-end production ML models to predict customer expansion and churn. Design automated retraining, monitoring, and incident response pipelines. Partner with engineering, product, and GTM teams on telemetry and data contracts. Run experiments, deliver analyses, and communicate findings to senior leadership to inform revenue strategy.

Design, deploy, and maintain large-scale ML workflows and knowledge graph services. Build production-ready LLM and RAG-based search pipelines, data ingestion/preprocessing, feature stores, monitoring, and security. Collaborate with cross-functional teams, document systems, research advanced ML/NLP techniques, optimize knowledge graph algorithms, and mentor junior engineers.