About this role
Lead, AI is a senior individual-contributor and technical leadership role in Ensemble Health Partners’ AI Innovation group, building production-grade AI and machine-learning systems for healthcare revenue cycle management (RCM). The position is based in Hyderabad or Bengaluru, with a stated shift of 2:30 PM–11:30 PM IST.
Responsibilities
- Design agentic AI architectures for multi-step RCM workflows, including decision-making guardrails, observability and controls. Integrate agents with enterprise data and revenue cycle systems; evaluate LLM and multi-agent orchestration frameworks; establish production monitoring, logging and incident response; and work with governance and compliance teams on responsible deployment.
- Consolidate client-specific models into reusable architectures, simplify ML pipelines, migrate from self-managed Airflow to managed orchestration, and remove redundant systems and processes. Document patterns that improve scalability and reliability.
- Lead code reviews, maintain exemplar code libraries, establish coding and design standards, and promote automated testing, CI/CD, security, Explainable AI and Clean Architecture. Mentor engineers through workshops, demonstrations and reviews.
- Assess and prioritize technical debt using static analysis and quality metrics, execute remediation, and report progress to leadership. Collaborate with architecture, product, compliance and security teams and communicate progress to business stakeholders.
Required qualifications
8–11 years of experience is listed for the role. Requirements also specify 8+ years of overall software engineering experience, 5+ years in analytics, data science or ML engineering, and 2+ years in a senior individual-contributor or technical lead role. Candidates need expert-level production Python, experience designing, deploying and operating production ML systems, strong code-review and engineering practices, and hands-on work with ML pipelines, ETL and data platforms.
Preferred qualifications
Healthcare RCM experience; exposure to LangGraph, AutoGen, CrewAI or Semantic Kernel; cloud ML platforms such as Azure ML, Databricks or Azure Data Factory; Clean Architecture and C4-style system design; model generalization through ensembles, transfer learning or multi-task learning; AI governance frameworks including NIST AI RMF, ISO 42001 or HITRUST; and static-analysis-based technical debt remediation. Stated benefits include health insurance for the associate, up to two children and parents; associate accident insurance; professional development reimbursement; and maternity and paternity benefits. The posting lists five positions.