Top AI & Machine Learning Jobs

Lead customer deployments of Moveworks ServiceNow AI Agents: design and build full-stack AI solutions, integrate and secure enterprise systems, tune LLM-based workflows, drive product adoption, collaborate with product and engineering, produce architecture and solution artifacts, and provide strategic customer guidance. Travel up to 25%.

Design, build, and operate production-grade agentic AI systems that reason over enterprise data, execute workflows, and run safely at scale. Focus areas include multi-agent orchestration, retrieval-grounded reasoning (RAG), model integration, observability, governance, and technical leadership to ship reliable, low-latency autonomous agents in production.

Lead development of a generative-AI-enabled enterprise search platform: architect abstractions, build ranking and multi-turn QA systems, integrate LLM and RAG features, create evaluation metrics, and mentor engineers and hiring processes.

Build, optimize, and scale ML infrastructure for training, evaluating, and serving large language models. Develop abstractions, productionize pipelines and microservices, improve LLM latency and monitoring, and collaborate cross-functionally to support enterprise ML systems at scale.

Scale and optimize a generative, agentic conversation engine for enterprise use: build product infrastructure and neutral APIs for chat clients, minimize latency and memory, enable private-domain knowledge and multilingual translation, implement logging/tracing/metrics, provide debugging tools, and collaborate with ML, product, and support teams.

Lead customer deployments of AI Agents on the Moveworks ServiceNow platform: design and build integrations, architect full-stack AI solutions, tune LLM-driven workflows, partner with product and engineering, and drive customer adoption and reusable templates.

Lead product vision and execution for an MVP autonomous agent platform, prototyping and shipping agentic capabilities. Own roadmap for orchestration, memory, action execution, and secure governance. Drive adoption, define metrics, partner with engineering, GTM, and open-source ecosystem, and translate frontier AI research into scalable platform primitives.

Lead engineering teams to build and ship the AI Control Tower platform: own roadmaps, drive 1.0-to-adoption, embed AI across development lifecycle, recruit and grow engineers, and align cross-functional partners to deliver scalable, cloud-native AI governance and observability for enterprise customers.

Lead and grow a global UX research organization focused on AI-driven product experiences. Define AI-native research strategies, embed modern evaluation and prompt-engineering practices, influence product and executive stakeholders, mentor managers, and translate research into actionable product decisions to improve generative AI workflows and employee experiences.

Design, build, and operate AI-native, industry-specific enterprise applications. Implement agentic behavior, prompt engineering, autonomous workflows, evaluation and testing for non-deterministic systems, and integrations at production scale. Mentor engineers, lead cross-team technical initiatives, work directly with customers when needed, and ensure safety, reliability, and performance in deployed systems.