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AI Tech Lead - Staff Machine Learning Engineer

1 month, 1 week ago
United States
Full-time
Lead
AI Engineer
Software Development
Apache Airflow AWS Azure Docker GCP Kubernetes LLM Machine Learning MLflow Python PyTorch System Design Vertex AI
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Sumo Logic

Sumo Logic

Sumo Logic offers top-tier cloud monitoring, log management, and Cloud SIEM tools for web and SaaS apps, empowering businesses with real-time insights and high-quality software delivery.

Internet Software & Services
251-1K
Founded 2010
View All Jobs 21

Description

  • Lead technical evaluation and adoption of agentic AI platforms and frameworks, including Anthropic, LangChain/LangGraph, AWS Bedrock, and emerging tools.
  • Architect, prototype, and productionize multi-agent AI systems for detection, triage, investigation, and response workflows.
  • Own core agent architecture components such as planning, execution, tool orchestration, memory, context engineering, and long-running workflows.
  • Lead offline and online evaluation pipelines for AI agents, including golden datasets, synthetic data generation, and human/LLM-based judging.
  • Drive LLM fine-tuning and alignment efforts to improve domain-specific reasoning, accuracy, and reliability.
  • Design scalable LLMOps and AI infrastructure for inference routing, latency optimization, cost control, and production observability.
  • Partner with product, security, and data platform teams to deliver end-to-end AI capabilities from prototype to customer-facing systems.
  • Provide technical direction and mentorship to AI engineers working on agentic AI and LLM systems.
  • Define and implement best practices for AI safety, reliability, evaluation, and monitoring in production.
  • Set technical direction for ambiguous problems and drive 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.
  • Strong foundation in machine learning, distributed systems, data pipelines, and large-scale system design.
  • Deep 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, including offline and online evaluation.
  • 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.
  • Hands-on experience building and scaling agentic AI systems or multi-agent architectures in production (preferred).
  • Experience with modern agent frameworks such as LangGraph, LangChain, CrewAI, or similar (preferred).
  • Experience with foundation model platforms such as Anthropic, OpenAI, AWS Bedrock, or Vertex AI (preferred).
  • Experience with LLM fine-tuning pipelines such as SFT, RLHF/RLAIF, preference learning, or domain adaptation (preferred).
  • Strong background in LLMOps, including inference optimization, latency/cost management, observability, and production monitoring (preferred).
  • Experience with tools such as PyTorch, MLflow, Airflow, Docker, Kubernetes, and cloud platforms like AWS, GCP, or Azure (preferred).
  • Experience applying AI/ML to security, observability, or large-scale log/telemetry data is a strong plus.
  • Must be authorized to work in the United States at the time of hire and for the duration of employment.
  • No non-immigrant visa sponsorship is available for this position.

Benefits

  • Eligible roles may participate in bonus or commission plans.
  • Eligible roles may receive equity awards.
  • Benefits offerings are available as part of the compensation package.
  • Compensation is variable based on role level, skills, qualifications, location, and experience.

Interested in this position?

Apply directly on the company website

Apply Now

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