Manager, AI Operations

Accountabilities:

• • Own the deployment support, day-to-day reliability, monitoring, and production operations of AI systems spanning traditional ML, Generative AI, and Agentic AI.
  • Lead incident response, troubleshooting, root-cause analysis, and remediation for AI/ML services, including systems capable of autonomous or tool-based actions.
  • Partner with MLOps, Cloud Engineering, Infrastructure, Security, and IT teams to establish robust deployment pipelines and production-ready operating practices.
  • Build and maintain comprehensive AI observability capabilities, including model drift detection, latency, uptime, performance degradation, logging, alerting, and agent-level tracing.
  • Define production health metrics and dashboards that provide real-time visibility into the performance, reliability, and operational risks of AI systems.
  • Establish processes for identifying performance issues and coordinating remediation with the appropriate AI development and data science teams.
  • Serve as the operational bridge between AI development teams and enterprise security, infrastructure, and technology functions, ensuring appropriate access controls and production risk management.
  • Support AI governance activities by implementing and operating measurable instrumentation for fairness, safety, bias, and other responsible-AI requirements defined by the governance function.
  • Coordinate the transition of AI solutions from development into production, including structured production-readiness reviews and operational handoffs.
  • Lead, develop, and mentor a small, high-leverage AI production support and observability team while establishing a strong operational and on-call culture.
  • Set priorities, manage capacity, and build scalable operational processes as the AI portfolio grows.
  • Lead cross-functional initiatives to establish ethical AI best practices and standard operating procedures across the design, development, and runtime layers of the AI stack.
  • Establish clear visibility into AI development and runtime costs and drive targeted year-over-year efficiency improvements.
  • Partner with Governance and Compliance teams to ensure AI standards are measurable, continuously monitored, and auditable through the observability platform.

  Requirements:

  • 7+ years of experience in AI/ML operations, MLOps, production data science, or a closely related discipline, including at least 2 years of people or team leadership experience.
  • Hands-on experience operating traditional machine learning and Generative AI systems in production, including deployment, monitoring, troubleshooting, and incident response.
  • Strong understanding of AI/ML observability practices, including model drift, performance monitoring, logging, alerting, uptime, latency, and production health metrics.
  • Experience partnering with Security and Infrastructure teams on production risk, access controls, operational readiness, and secure deployment practices.
  • Strong communication and stakeholder-management skills, with the ability to translate complex technical and operational risks into clear business terms.
  • Demonstrated ability to lead teams, prioritize competing initiatives, manage capacity, and establish effective operational processes.
  • Experience working across technical and business functions in a fast-moving, collaborative environment.
  • Prior experience in healthcare, health technology, payer, or provider organizations is preferred.
  • Experience operating Agentic AI systems, including tool-use monitoring, guardrails, and action-level tracing, is a strong advantage.
  • Familiarity with AI/ML observability and cloud technologies such as Datadog, AWS CloudWatch, Langfuse, and native AWS capabilities is preferred.
  • Experience working alongside a dedicated AI Governance function, with a clear understanding of the distinction between operational monitoring and governance policy, is desirable.
  • Strong interest in responsible and ethical AI, operational risk management, cost optimization, and building scalable AI practices.

  Benefits:

  • Comprehensive medical, dental, and vision insurance.
  • 401(k) retirement plan with company matching.
  • Flexible paid time off.
  • Paid parental leave.
  • HSA and FSA options.
  • Educational reimbursement program.
  • Employer-paid Employee Assistance Program and mental health services.
  • Professional development opportunities in a growing AI and healthcare technology environment.
  • Collaborative, fast-moving culture with opportunities to make a measurable impact on AI operations and healthcare efficiency.
  • Travel to the company’s Tennessee offices for training as required.
  • U.S. work authorization is required; visa sponsorship or immigration support is not provided for this position.