Lead Machine Learning Engineer

AI Tech Lead - Staff Machine Learning EngineerThe 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.ResponsibilitiesLead and partner with fellow leadership members and teams on technical evaluation and adoption of cutting-edge agentic AI platforms.Architect, prototype, and productionize multi-agent AI systems for Agentic SOC use cases.Own the design of core agent architecture components.Lead AI agent evaluation systems.Drive LLM fine-tuning and alignment efforts.Design scalable LLMOps and AI agent infrastructure.Partner with product, security, and data platform leadership and teams.Lead and partner on technical direction and mentorship for AI engineers.Define and implement best practices for AI safety, reliability, evaluation, and monitoring.Operate as a senior technical owner in ambiguous problem spaces.Required QualificationsB.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.Desired QualificationsHands-on experience building and scaling agentic AI systems or multi-agent architectures in production.Experience with modern agent frameworks such as LangGraph, LangChain, CrewAI, or similar.Experience with major foundation model platforms such as Anthropic, OpenAI, AWS Bedrock, or Vertex AI.Experience with LLM fine-tuning pipelines (SFT, RLHF/RLAIF, preference learning, domain adaptation).Strong background in LLMOps, including inference optimization, latency/cost management, observability, and production monitoring.Experience with ML infrastructure and tooling such as PyTorch, MLflow, Airflow, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).Experience applying AI/ML to security, observability, or large-scale log/telemetry data is a strong plus.