The COO will work closely with engineering, data science, clinical operations, and deployment teams to build scalable AI infrastructure and operational intelligence platforms that solve real-world healthcare challenges.

Key Responsibilities :

- Define the technical architecture, roadmap, and execution strategy for operational AI agents across healthcare practices.

- Lead development of AI-driven operational systems including :

1. Financial Margin Optimization Agent

2. Supply Chain Intelligence Agent

3. Scheduling & Workforce Optimization Agent

4. Clinical Training & Outcomes Intelligence Agent

- Create detailed Product Requirement Documents (PRDs), workflow specifications, and system architecture documentation.

- Partner with engineering teams to build multi-agent systems and operational decision intelligence platforms.

- Drive development of autonomous AI workflows capable of orchestrating operational processes end-to-end.

- Lead the implementation of AI agents powered by Large Language Models (LLMs) for healthcare operations.

- Define scalable architectures using modern AI agent frameworks such as :

1. LangGraph

2. AutoGen

3. CrewAI

4. Agent Development Kits (ADKs)

5. Multi-step reasoning workflows

6. Task orchestration

7. Automated operational decision-making

8. Healthcare-specific automation use cases

- Collaborate with AI engineering teams to optimize model performance, reliability, and scalability.

Healthcare Data Infrastructure & Intelligence Platforms :

- Build and scale enterprise-grade healthcare data platforms integrating :

1. Revenue cycle and billing platforms

2. Practice management systems

3. Scheduling and workforce systems

- Oversee development of real-time data pipelines and operational analytics infrastructure.

- Lead implementation of healthcare intelligence layers and operational data warehouses.

- Drive adoption of modern data stack technologies including :

1. Snowflake / BigQuery / Redshift

2. Apache Airflow / Dagster

3. dbt and ETL frameworks

- Python-based data pipelines

- Lead deployment of AI platforms across real-world healthcare practices and operational environments.

- Electronic Health Record (EHR) systems

- Practice Management Systems

- Revenue Cycle Management platforms

- Scheduling and staffing systems

- Oversee Forward Deployed Engineering teams responsible for onsite implementation and adoption.

- Ensure successful operationalization of AI systems across acquired healthcare entities.

- Design and deploy AI-powered operational automation systems across healthcare functions including :

1. Documentation automation

2. Insurance claims processing

3. Clinical workflow optimization

- Develop AI copilots to improve productivity and reduce administrative burden for healthcare staff.

- Drive automation initiatives that enhance operational efficiency, accuracy, and scalability.

Analytics, Metrics & Operational Intelligence :

- Build data-driven dashboards and operational intelligence systems to measure business impact of AI adoption.

- Denial rate reduction

- Revenue cycle performance

- Documentation efficiency

- Staff productivity improvements

- Operational cost savings

- EBITDA growth

- Implement feedback loops and continuous improvement systems using real-world operational data.

Cross-Functional Leadership & AI Engineering Collaboration :

- Partner closely with engineering, data science, product, and healthcare operations teams.

- Ensure AI solutions are aligned with operational realities and measurable business outcomes.

- Drive continuous iteration and model improvement through deployment feedback and operational insights.

- Lead execution across technical, operational, and implementation functions.

Preferred Qualifications :

- Bachelors or Masters degree in Computer Science, Engineering, Data Science, Healthcare Informatics, or related field.

- 12+ years of experience in technology, AI systems, healthcare operations, or enterprise platform leadership.

- Strong experience building and deploying AI/LLM-based systems in production environments.

- Deep understanding of healthcare operational workflows and healthcare technology ecosystems.

- Experience with :

1. Multi-agent AI systems

2. AI deployment infrastructure

3. Healthcare data platforms

4. Operational automation systems

5. Enterprise analytics platforms

- Strong leadership experience managing cross-functional technical and operational teams