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AI Tech Lead - Staff Machine Learning Engineer

1 month, 4 weeks 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
Apply Now
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 18

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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