Manager, AI Operations

Xsolisis an AI-driven technology company reducing administrative waste in healthcare by enabling smarter collaboration between providers and payers. Since 2013, our vision has been to create a frictionless healthcare system.

We are proudly headquartered in Franklin, TN - one of the nation's fastest-growing hubs for healthcare innovation - we are at the heart of a thriving ecosystem of health systems, payers, and technology leaders.

Our flagship product,Dragonfly®, is the first and only AI-driven platform to continuously assign real-time predictive scores for medical necessity. Dragonfly has delivered proven results across 600+hospital, health system, and health plan clients and earned repeated industry recognition.

With recognition on theInc.
5000andDeloitte Technology Fast 500lists,Xsolisis also one of the fastest-growing privately-held companies in the country and across North America, andwe'relooking for talented people to grow with us.

Position Summary Details
We are seeking an experienced AI Operations leader to own the reliability, performance, and observability of our AI portfolio in production — spanning traditional machine learning, Generative AI, and Agentic AI systems. This role is ideal for a technically strong manager who thinks in terms of uptime, drift, and risk, and who can translate models and agents built by our data science teams into scalable, monitored, and secure production systems.
You will lead a team responsible for AI production support, observability, and the operational connective tissue between our AI build organization, security, and infrastructure functions
to lead tactical and strategic roadmap for us to become a leader in “Ethical AI”. This role does not own model development or AI governance policy — it owns making sure everything we ship runs well, is visible, and is safe to operate at scale.

Essential Duties & Responsibilities
The essential functions include, but are not limited to the following:

1. AI Production Operations

• Own deployment support, monitoring, and day-to-day reliability of AI systems in production across traditional ML, GenAI, and agentic AI.
• Lead incident response and root-cause troubleshooting for AI/ML services, including agentic systems with autonomous or tool-using behavior.
• Partner with MLOps, Cloud Engineering, and Infrastructure teams to build and maintain robust deployment pipelines.

2. Observability & Model Performance Monitoring

• Build and maintain observability practices (drift detection, latency, uptime, accuracy decay, agent action-level tracing) across all AI system types.
• Define and track production health metrics; flag performance degradation and route it to the appropriate build team for remediation.
• Establish dashboards and alerting that give the organization real-time visibility into AI system health.

3. Security & Cross-Functional Liaison

• Serve as the primary connection point between AI systems and enterprise Security, Infrastructure, and IT teams — ensuring production AI meets security and access-control standards.
• Support the AI Governance function by instrumenting and operating the fairness, safety, and bias-monitoring metrics it defines (governance sets the requirement; this team builds and runs the instrumentation).
• Coordinate handoffs from the AI Build team into production, including a defined production-readiness review before launch.
• Lead and grow a small, high-leverage production support and observability team.
• Set clear priorities across production support and monitoring work streams and manage team capacity as the AI portfolio scales.
• Mentor team members and build a strong operational and on-call culture.

5.Establish Xsolis as “Ethical AI Leader” in our space

• Lead cross functional team to assess what is required in design, dev and run-time across our entire AI stack to establish “Ethical AI” best practices and SOPs for Xsolis
• Ensure the Cost of AI Dev and Run-time is clear and targeted for specific annual reduction YoY
• Work with Governance and Compliance team to set standards that are measurable, monitored and auditable through the observability platform across Traditional, Generative and Agentic AI.

Minimum Qualifications (Knowledge,…