I'm Saroj Kumandan, a Senior AI/ML Engineer with 8+ years of experience delivering scalable AI/ML platforms, distributed data systems, and Generative AI solutions across healthcare, financial services, and large-scale enterprises. I build production-grade LLMs, RAG, semantic search, and AI-powered workflows using LangChain, LangGraph, vector search architectures, and cloud-native frameworks to enable AI-assisted operations, enterprise knowledge retrieval, and real-time decision support. My work combines ML, data engineering, and governance to ship end-to-end AI solutions. I lead MLOps and LLMOps, implement retrieval-quality evaluation, model explainability, and robust monitoring to drive reliability and regulatory compliance in banking and healthcare environments, while delivering scalable APIs and cloud-native microservices for secure, low-latency AI applications.

Saroj Kumandan

I'm Saroj Kumandan, a Senior AI/ML Engineer with 8+ years of experience delivering scalable AI/ML platforms, distributed data systems, and Generative AI solutions across healthcare, financial services, and large-scale enterprises. I build production-grade LLMs, RAG, semantic search, and AI-powered workflows using LangChain, LangGraph, vector search architectures, and cloud-native frameworks to enable AI-assisted operations, enterprise knowledge retrieval, and real-time decision support. My work combines ML, data engineering, and governance to ship end-to-end AI solutions. I lead MLOps and LLMOps, implement retrieval-quality evaluation, model explainability, and robust monitoring to drive reliability and regulatory compliance in banking and healthcare environments, while delivering scalable APIs and cloud-native microservices for secure, low-latency AI applications.

Available to hire

I’m Saroj Kumandan, a Senior AI/ML Engineer with 8+ years of experience delivering scalable AI/ML platforms, distributed data systems, and Generative AI solutions across healthcare, financial services, and large-scale enterprises. I build production-grade LLMs, RAG, semantic search, and AI-powered workflows using LangChain, LangGraph, vector search architectures, and cloud-native frameworks to enable AI-assisted operations, enterprise knowledge retrieval, and real-time decision support.

My work combines ML, data engineering, and governance to ship end-to-end AI solutions. I lead MLOps and LLMOps, implement retrieval-quality evaluation, model explainability, and robust monitoring to drive reliability and regulatory compliance in banking and healthcare environments, while delivering scalable APIs and cloud-native microservices for secure, low-latency AI applications.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
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Work Experience

Senior AI/ML Engineer at McKesson Corporation
January 1, 2024 - Present
Developed HIPAA-compliant Enterprise Generative AI, Intelligent Search, and Knowledge Retrieval platforms for pharmacy operations, oncology analytics, clinical support workflows, and enterprise knowledge management. Implemented production-grade RAG, Semantic Search, Agentic AI, and LLMOps on Google Cloud Platform using LangChain, LangGraph, Vertex AI, and cloud-native microservices. Processed and indexed over 2M+ clinical documents and enterprise assets to improve information access, decision support, and operational efficiency. Built multilingual voice capabilities with Whisper and ElevenLabs, and established LLM evaluation/benchmarking with RAGAS and hallucination monitoring to reduce production issues.
AI/ML Engineer at JPMorgan Chase
November 1, 2021 - August 1, 2023
Developed cloud-native ML pipelines for fraud analytics, transaction monitoring, AML compliance, and risk intelligence. Engineered data ingestion/ETL with PySpark, Kafka, and AWS Glue; built fraud detection models with XGBoost and Scikit-learn; implemented hybrid retrieval with OpenSearch/FAISS for AML case workflows; deployed distributed microservices with FastAPI, Docker, and Kubernetes. Established MLOps using MLflow, SageMaker, GitHub Actions, and Terraform; implemented drift detection and SHAP-based explainability for regulated banking environments.
Data Scientist at Tenet Healthcare
May 1, 2019 - October 1, 2021
Contributed to healthcare ML and predictive analytics for patient risk stratification, readmission analysis, and care management. Built HIPAA-compliant pipelines with PySpark, Azure Databricks, and Delta Lake; developed NLP workflows for clinical notes via spaCy/scispaCy; applied XGBoost and Scikit-learn for predictive modeling; enabled reporting with Power BI and ensured data governance with HIPAA-compliant controls.
Data Engineer at Uber
June 1, 2017 - April 1, 2019
Contributed to backend data engineering and distributed analytics for ride operations and driver allocation. Built batch and near real-time pipelines using PySpark, Kafka, Airflow; engineered data transformation with Hive/Presto on HDFS/YARN; developed Python-based data services and monitoring dashboards with Grafana to support operational analytics and reporting.

Education

Master of Professional Studies, Data Science at University of Maryland, Baltimore County (UMBC)
January 11, 2030 - June 29, 2026

Qualifications

AWS Certified Machine Learning – Specialty
January 11, 2030 - June 29, 2026
Microsoft Certified: Azure AI Engineer Associate
January 11, 2030 - June 29, 2026
Microsoft Certified: Azure Data Engineer Associate
January 11, 2030 - June 29, 2026
Databricks Generative AI Fundamentals
January 11, 2030 - June 29, 2026
Google Cloud Professional Machine Learning Engineer
January 11, 2030 - June 29, 2026

Industry Experience

Healthcare, Financial Services, Software & Internet