Manager, AI Operations

New
J
JobgetherHealthcare Technology
Based in the United StatesFull-TimeManager
Salary not disclosed
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Job Details

Experience
7+ years
Required Skills
AWSDatadogMLOpsGenerative AI

Requirements

  • 7+ years of experience in AI/ML operations, MLOps, production data science, or a closely related discipline.
  • At least 2 years of people or team leadership experience.
  • Hands-on experience operating traditional machine learning and Generative AI systems in production.
  • Strong understanding of AI/ML observability practices including drift, performance monitoring, and alerting.
  • Experience partnering with Security and Infrastructure teams on production risk and access controls.
  • Strong communication and stakeholder-management skills.
  • Demonstrated ability to lead teams, prioritize initiatives, and manage capacity.
  • Experience operating Agentic AI systems, including tool-use monitoring and guardrails.
  • Familiarity with cloud technologies and observability platforms like Datadog, AWS CloudWatch, or Langfuse.
  • Experience working alongside dedicated AI governance functions.

Responsibilities

  • Own the deployment support, day-to-day reliability, monitoring, and production operations of AI systems.
  • Lead incident response, troubleshooting, root-cause analysis, and remediation for AI/ML services.
  • Partner with MLOps, Cloud, Infrastructure, and Security teams to establish robust deployment pipelines.
  • Build and maintain comprehensive AI observability capabilities, including drift detection, latency, and uptime monitoring.
  • Define production health metrics and dashboards for real-time visibility into performance and risks.
  • Lead, develop, and mentor a high-leverage AI production support and observability team.
  • Coordinate the transition of AI solutions from development into production via readiness reviews.
  • Support AI governance by implementing measurable instrumentation for fairness, safety, and bias.
  • Establish clear visibility into AI development and runtime costs to drive efficiency.
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