Staff Machine Learning Engineer, Sumo Logic

• B.Tech, M.Tech, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related technical field
• 5+ years of hands-on industry experience building, operating, and leading production ML/AI systems, with demonstrated technical leadership and ownership
• Strong foundation in machine learning, distributed systems, data pipelines, and large-scale system design
• Deep industry understanding of LLMs, prompt engineering, context engineering, agentic AI design patterns, and reasoning workflows
• Strong proficiency in Python and modern ML/AI ecosystems
• Experience designing and operating evaluation frameworks for ML/LLM systems (offline + online)
• Proven ability to lead complex technical initiatives across teams and influence architecture decisions
• Excellent communication skills and ability to translate complex AI systems into business impact

Desirable

• 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 global scale
• As a Staff Machine Learning Engineer – AI Tech Lead, you will lead the design and delivery of the next generation of Agentic AI systems for Security Operation 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
• 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 evaluation systems, including offline and online evaluation pipelines, golden datasets, synthetic data generation, human- and LLM-based judging, and continuous quality monitoring
• Drive LLM fine-tuning and alignment efforts to improve domain-specific reasoning, accuracy, and reliability for security and observability use cases
• Design scalable LLMOps and AI agent infrastructure, including inference routing, latency optimization, cost control, and production observability for agent systems
• Partner with product, security, and data platform leadership and teams to deliver end-to-end AI agent capabilities from prototype to customer-facing production systems
• Lead and partner on technical direction and mentorship for AI engineers working on agentic AI and LLM systems
• Define and implement best practices for AI safety, reliability, evaluation, and monitoring in production agentic systems
• Operate as a senior technical owner in ambiguous problem spaces—setting technical direction, breaking down complex problems, and driving delivery across teams