Lead, AI

Job highlights

• Experience with cloud-based ML platforms (Azure ML,Databricks,Azure Data Factory,or similar) . Strong understanding of Clean Architecture and system design (C4 or equivalent) .
• Preferred Qualifications .
• Experience in healthcare revenue cycle management (RCM) .
• Experience with model generalization techniques (ensembles,transfer learning,multi-task learning) .

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, Compliance, and Security teams to deliver compliant AI solutions

Translate complex technical work into clear progress updates for business stakeholders

Lead cross-team knowledge sharing and technical communities of practice

Required Qualifications

8+ years of overall software engineering experience

5+ years in analytics, data science, or ML engineering roles

2+ years in a senior IC or technical lead role

Expert-level Python development with strong focus on production-quality code

Proven experience designing, deploying, and operating ML systems in production

Strong background in code reviews, quality standards, and engineering best practices

Hands-on experience with ML pipelines, ETL workflows, and data platforms

Preferred Qualifications

Experience in healthcare revenue cycle management (RCM)

Exposure to agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel)

Experience with cloud-based ML platforms (Azure ML, Databricks, Azure Data Factory, or similar)

Strong understanding of Clean Architecture and system design (C4 or equivalent)

Experience with model generalization techniques (ensembles, transfer learning, multi-task learning)

Familiarity with AI governance and compliance frameworks (NIST AI RMF, ISO 42001, HITRUST)

Experience quantifying and remediating technical debt using static analysis tools

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