Staff Machine Learning Engineer – AI Tech Lead
Sumo Logic
full-time
Posted on:
Location Type: Remote
Location: United States
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Job Level
Tech Stack
About the role
- 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.
Requirements
- 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.
Benefits
- Compensation varies based on a variety of factors, which include (but aren’t limited to) role level, skills and competencies, qualifications, knowledge, location, and experience.
- In addition to base pay, certain roles are eligible to participate in our bonus or commission plans, as well as our benefits offerings and equity awards.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Pythonmachine learningdistributed systemsdata pipelineslarge-scale system designLLM fine-tuningcontext engineeringevaluation frameworksAI safetyagent architecture design
Soft Skills
technical leadershipmentorshipcommunicationproblem-solvinginfluencecollaborationtechnical directioncomplex initiative leadershipdelivery across teamstranslating technical concepts
Certifications
B.TechM.TechPh.D.