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I am an AI/ML engineer with over a decade of experience designing, deploying, and operationalizing Generative AI and machine learning solutions across healthcare, finance, and enterprise analytics. I specialize in cloud-native AI development on AWS and Google Cloud, building scalable MLOps pipelines and delivering production-grade models that drive measurable business value. I lead cross-functional teams to implement governance, HIPAA/PHI compliance, and end-to-end GenAI solutions—from data prep and model training to observability, retrieval, and explainability. I focus on practical, explainable AI that enables self-service analytics and data-driven decision making, while optimizing performance, cost, and reliability at scale.…I am an AI/ML engineer with over a decade of experience designing, deploying, and operationalizing Generative AI and machine learning solutions across healthcare, finance, and enterprise analytics. I specialize in cloud-native AI development on AWS and Google Cloud, building scalable MLOps pipelines and delivering production-grade models that drive measurable business value. I lead cross-functional teams to implement governance, HIPAA/PHI compliance, and end-to-end GenAI solutions—from data prep and model training to observability, retrieval, and explainability. I focus on practical, explainable AI that enables self-service analytics and data-driven decision making, while optimizing performance, cost, and reliability at scale.

Mani Sharath Chandra

AI Engineer, Data Scientist, Full Stack Developer, +1

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I am an AI/ML engineer with over a decade of experience designing, deploying, and operationalizing Generative AI and machine learning solutions across healthcare, finance, and enterprise analytics. I specialize in cloud-native AI development on AWS and Google Cloud, building scalable MLOps pipelines and delivering production-grade models that drive measurable business value. I lead cross-functional teams to implement governance, HIPAA/PHI compliance, and end-to-end GenAI solutions—from data prep and model training to observability, retrieval, and explainability. I focus on practical, explainable AI that enables self-service analytics and data-driven decision making, while optimizing performance, cost, and reliability at scale.…I am an AI/ML engineer with over a decade of experience designing, deploying, and operationalizing Generative AI and machine learning solutions across healthcare, finance, and enterprise analytics. I specialize in cloud-native AI development on AWS and Google Cloud, building scalable MLOps pipelines and delivering production-grade models that drive measurable business value. I lead cross-functional teams to implement governance, HIPAA/PHI compliance, and end-to-end GenAI solutions—from data prep and model training to observability, retrieval, and explainability. I focus on practical, explainable AI that enables self-service analytics and data-driven decision making, while optimizing performance, cost, and reliability at scale.

Available to hire

I am an AI/ML engineer with over a decade of experience designing, deploying, and operationalizing Generative AI and machine learning solutions across healthcare, finance, and enterprise analytics. I specialize in cloud-native AI development on AWS and Google Cloud, building scalable MLOps pipelines and delivering production-grade models that drive measurable business value.

I lead cross-functional teams to implement governance, HIPAA/PHI compliance, and end-to-end GenAI solutions—from data prep and model training to observability, retrieval, and explainability. I focus on practical, explainable AI that enables self-service analytics and data-driven decision making, while optimizing performance, cost, and reliability at scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AI/ML Engineer at Transcarent

December 1, 2024 - November 25, 2025

Designed and deployed end-to-end ML pipelines on Google Cloud Platform (BigQuery, Vertex AI, Cloud Functions) to process HIPAA-compliant EHR datasets from Cerner, Epic, and Athena; built Vertex AI feature stores for churn, fraud, and medication adherence models; developed LLM-enabled document understanding for structured requirement templates and SQL-generation for self-service analytics; fine-tuned foundation models using SageMaker and Hugging Face; deployed offline NLP models on Databricks with PyTorch and MLflow; established MLOps pipelines with Airflow, Terraform, and Vertex AI for CI/CD and automated deployment; built REST APIs with FastAPI/Flask; integrated Databricks and Delta Lake across Azure and GCP for cross-cloud training; implemented real-time data quality and drift detection; established governance and lineage using Neo4j; implemented LLM observability with LangSmith and LangFuse; automated CI/CD with GitHub Actions; created LLM-enabled enterprise interfaces using React/N

AI/ML Developer at Experian

November 1, 2024 - November 1, 2024

Designed and implemented customer segmentation and predictive models using Python and Redshift; built ML pipelines for fraud detection, churn, and anomaly detection with PySpark/Scikit-Learn; integrated Kafka/Kinesis streaming with Delta Lake for near-real-time inference; orchestrated training and deployment with SageMaker Pipelines, Airflow, and MLflow; optimized preprocessing and feature engineering for large financial datasets; integrated ML KPIs into Power BI dashboards and leveraged LlamaIndex/LangChain for document indexing in GenAI pipelines; collaborated with stakeholders to translate business goals into AI capabilities and automated governance via Dataiku pipelines.

Data Scientist at Citrix

February 1, 2023 - February 1, 2023

Analyzed clickstream and usage data in Azure SQL to build churn prediction and retention models; engineered time-series and behavioral data pipelines in Azure Databricks; applied anomaly detection, trend forecasting, and user segmentation; enhanced large-scale ETL/ML pipelines in Spark; built predictive dashboards in Power BI; implemented real-time anomaly detection with Azure Stream Analytics; performed AIOps analytics for SLA breach prediction and root-cause automation; ensured data governance and secure model access via Azure Key Vault.

Data Engineer at WNS Global Services

February 1, 2021 - February 1, 2021

Engineered and optimized SQL/ETL pipelines in Amazon Redshift for high-performance analytics; built Python and PySpark data workflows for schema validation, anomaly detection, and data standardization; designed and managed AWS Glue and Lambda ETL jobs transforming large JSON/Parquet datasets; orchestrated Airflow DAGs with Jenkins CI/CD; developed data lake/warehouse layers using Redshift, S3, and Athena; implemented data quality and lineage with Glue Catalog and Lake Formation; collaborated with DevOps to deploy infrastructure using Terraform and CloudFormation; supported regulated environments with governance and SLA adherence.

Associate Data Analyst at EVRY India Pvt Limited

July 1, 2018 - July 1, 2018

Developed Oracle SQL queries and data models to support healthcare and HR analytics; built SSRS, Power BI, Tableau, and Excel reporting pipelines with dynamic ranges, DAX, macros, and role-based security; automated KPI reporting with Excel dashboards; validated ETL outputs from Informatica and Talend; applied Python (Pandas) for survey data cleaning and transformation; documented data flows and governance in Lucidchart/Confluence, ensuring consistency and compliance across reporting pipelines.