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AI Tech Lead - Staff Machine Learning Engineer

Sumo Logic·US·United States·senior
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AI Tech Lead - Staff Machine Learning Engineer Location: USA The proliferation of AI and machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and security operations. With this opportunity comes significant technical challenges around ingesting, managing, and reasoning over massive, heterogeneous, high-velocity data streams at a global scale. As an AI Tech Lead , you will lead the design and delivery of the next generation of Agentic AI systems for the Security Operations Center (Agentic SOC). You will evaluate, prototype, and productionize state-of-the-art agentic AI technologies and build scalable multi-agent architectures that reason over large-scale machine data to drive real-time detection, investigation, and response. This is a highly technical leadership role with deep ownership of AI agent architecture, evaluation, LLM fine-tuning, and production AI infrastructure. You will help define the technical direction for Sumo Logic’s agentic AI platform and play a key role in bringing advanced AI capabilities to customers at global scale. - Sumo Logic has a strong competitive advantage in the rapidly evolving AI space because we not only have an established enterprise customer base, we also own and manage a vast amount of operational and data, a critical advantage for building and improving AI-driven capabilities. Responsibilities Lead and partner with fellow leadership members and teams on technical evaluation and adoption of cutting-edge agentic AI platforms, including Anthropic (Claude), LangChain/LangGraph, AWS Bedrock, and other emerging agent frameworks. Architect, prototype, and productionize multi-agent AI systems for Agentic SOC use cases, including detection, triage, investigation, and response workflows. Own the design of core agent architecture components, including planning, execution, tool orchestration, memory, context engineering, and long-running agent workflows. Lead AI agent evaluati

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