Lead AI

Job Title: Lead, AI

Experience: 8-11 Years

Location: Hyderabad and Bengaluru

Company Overview:

Ensemble Health Partners India is at the forefront of innovation in the Revenue Cycle Management (RCM) space, leveraging modern technology to drive meaningful, real world impact. Our future ready platforms bring together AI driven analytics , intelligent data ingestion, workflow automation, and business intelligence built on a scalable, cloud native architecture. Our AI powered solutions are actively running in production, continuously optimizing processes and delivering data driven insights at scale. With the second largest market share in the U.S. RCM industry, a global workforce of 15,000+ professionals, and 12 technology patents , we deliver results through strong teams, proven processes, and flexible, modern technologies. As part of our continued growth, we have launched our Global Capability Center (GCC) in Hyderabad designed to serve as a strategic extension of our global operations. The GCC brings together technology, analytics, and RCM expertise to build scalable solutions, accelerate innovation, and support our long term vision of transforming healthcare operations. At Ensemble Health Partners India, we foster a culture of growth, collaboration, and innovation where your expertise is valued, your ideas are heard, and your work makes a measurable impact.

Position Summary:

Ensemble Health Partners is looking for a highly experienced Lead – Analytics to join our AI Innovation group. This is a senior individual contributor and technical leadership role, focused on building production-grade AI and ML systems that transform healthcare revenue cycle management (RCM).

In this role, you will lead engineering excellence across analytics and ML platforms, drive agentic AI development, execute radical simplification of complex ML pipelines, and systematically reduce technical debt. You will work closely with architecture, product, compliance, and engineering teams to deliver scalable, secure, and high-impact AI solutions.

This role is ideal for someone who combines deep hands-on technical expertise with strong influence, mentorship, and a passion for clean, maintainable, and high-quality engineering.

Key Responsibilities

1. Agentic AI Development

Design and implement agentic AI architectures that autonomously execute complex, multi-step RCM workflows

Build decision-making systems with strong guardrails, observability, and control mechanisms

Integrate autonomous AI agents with enterprise data platforms and revenue cycle systems

Evaluate and implement LLM-based and multi-agent frameworks for orchestration

Establish production-grade monitoring, logging, and incident response for AI agents

Partner with governance and compliance teams to ensure responsible AI deployment

2. Radical Simplification & Execution

Lead large-scale model consolidation initiatives, reducing client-specific ML models into generalized, reusable architectures

Simplify ML pipelines and reduce operational complexity across the analytics platform

Drive migration from self-managed Airflow to managed orchestration solutions

Identify and eliminate redundant systems, code, and processes to improve scalability and reliability

Document and evangelize simplification patterns across the organization

3. Code Craftsmanship & Engineering Excellence

Own and lead rigorous code review practices with a focus on quality, security, and maintainability

Create and maintain exemplar code libraries showcasing best practices and performance optimization

Define, implement, and enforce coding standards, design patterns, and Clean Architecture principles

Drive adoption of automated testing, CI/CD pipelines, and quality tooling

Champion security, Explainable AI (XAI), and responsible engineering as core principles

Mentor and upskill engineers through workshops, demos, and hands-on code reviews

4. Technical Debt Reduction

Conduct detailed technical debt assessments using static analysis and quality metrics

Prioritize and execute debt reduction initiatives aligned with business impact

Prevent future debt through strong engineering discipline and design reviews

Track and report technical debt metrics to leadership on a regular cadence

5. Cross-Functional Collaboration

Work closely with Architecture Leads to ensure alignment with Clean Architecture standards

Partner with Product, Complianc…