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I am an AI/ML engineer with 7+ years of delivering enterprise-grade AI/ML, Generative AI, and data-engineering solutions across healthcare, finance, and regulatory domains. I architect and operationalize end-to-end intelligent ecosystems—from data ingestion and feature engineering to model governance, deployment, and observability—across cloud-native environments (AWS, Azure, GCP). I don’t just fine-tune models; I design scalable, compliant systems that deliver measurable business impact with explainability and regulatory trust. My hands-on practice spans large-language models, retrieval-augmented generation (RAG), and data pipelines. I work with LangChain, LangGraph, CrewAI, Azure OpenAI, Bedrock, and Hugging Face Transformers to build multi-agent workflows and governance frameworks. I bridge theory and production by implementing MLOps, drift monitoring, and observability dashboards, while collaborating across teams to deliver secure, auditable AI solutions for regulated industries.…I am an AI/ML engineer with 7+ years of delivering enterprise-grade AI/ML, Generative AI, and data-engineering solutions across healthcare, finance, and regulatory domains. I architect and operationalize end-to-end intelligent ecosystems—from data ingestion and feature engineering to model governance, deployment, and observability—across cloud-native environments (AWS, Azure, GCP). I don’t just fine-tune models; I design scalable, compliant systems that deliver measurable business impact with explainability and regulatory trust. My hands-on practice spans large-language models, retrieval-augmented generation (RAG), and data pipelines. I work with LangChain, LangGraph, CrewAI, Azure OpenAI, Bedrock, and Hugging Face Transformers to build multi-agent workflows and governance frameworks. I bridge theory and production by implementing MLOps, drift monitoring, and observability dashboards, while collaborating across teams to deliver secure, auditable AI solutions for regulated industries.

HEMANTH KOPPAKA

AI Engineer, Data Scientist, Full Stack Developer, +2

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I am an AI/ML engineer with 7+ years of delivering enterprise-grade AI/ML, Generative AI, and data-engineering solutions across healthcare, finance, and regulatory domains. I architect and operationalize end-to-end intelligent ecosystems—from data ingestion and feature engineering to model governance, deployment, and observability—across cloud-native environments (AWS, Azure, GCP). I don’t just fine-tune models; I design scalable, compliant systems that deliver measurable business impact with explainability and regulatory trust. My hands-on practice spans large-language models, retrieval-augmented generation (RAG), and data pipelines. I work with LangChain, LangGraph, CrewAI, Azure OpenAI, Bedrock, and Hugging Face Transformers to build multi-agent workflows and governance frameworks. I bridge theory and production by implementing MLOps, drift monitoring, and observability dashboards, while collaborating across teams to deliver secure, auditable AI solutions for regulated industries.…I am an AI/ML engineer with 7+ years of delivering enterprise-grade AI/ML, Generative AI, and data-engineering solutions across healthcare, finance, and regulatory domains. I architect and operationalize end-to-end intelligent ecosystems—from data ingestion and feature engineering to model governance, deployment, and observability—across cloud-native environments (AWS, Azure, GCP). I don’t just fine-tune models; I design scalable, compliant systems that deliver measurable business impact with explainability and regulatory trust. My hands-on practice spans large-language models, retrieval-augmented generation (RAG), and data pipelines. I work with LangChain, LangGraph, CrewAI, Azure OpenAI, Bedrock, and Hugging Face Transformers to build multi-agent workflows and governance frameworks. I bridge theory and production by implementing MLOps, drift monitoring, and observability dashboards, while collaborating across teams to deliver secure, auditable AI solutions for regulated industries.

Available to hire

I am an AI/ML engineer with 7+ years of delivering enterprise-grade AI/ML, Generative AI, and data-engineering solutions across healthcare, finance, and regulatory domains. I architect and operationalize end-to-end intelligent ecosystems—from data ingestion and feature engineering to model governance, deployment, and observability—across cloud-native environments (AWS, Azure, GCP). I don’t just fine-tune models; I design scalable, compliant systems that deliver measurable business impact with explainability and regulatory trust.

My hands-on practice spans large-language models, retrieval-augmented generation (RAG), and data pipelines. I work with LangChain, LangGraph, CrewAI, Azure OpenAI, Bedrock, and Hugging Face Transformers to build multi-agent workflows and governance frameworks. I bridge theory and production by implementing MLOps, drift monitoring, and observability dashboards, while collaborating across teams to deliver secure, auditable AI solutions for regulated industries.

Skills

Experience Level

Expert

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Expert

Language

English

Fluent

Work Experience

AI Engineer at Cigna-Evernorth

July 1, 2024 - Present

Built LangGraph-based multi-agent workflows on Azure OpenAI to automate eligibility, claims validation, and clinical insight generation, streamlining provider and member workflows under HIPAA compliance. Implemented Python + FastAPI microservices for eligibility checks, claim validation, provider search, and RAG orchestration with clean domain separation and async API performance. Engineered Python + PySpark ETL across PostgreSQL, MSSQL, and ADLS Gen2 with Kafka/Event Hubs to boost ingestion throughput by ~40%. Standardized schema definitions and data contracts for claims/pharmacy feeds to ensure reliable embeddings for retrieval pipelines. Designed hybrid RAG pipelines unifying retrieval across EOB, FHIR/HL7, PDFs, and SQL sources to improve contextual accuracy by 29%. Implemented adaptive chunking and dynamic Top-K retrieval to reduce GPT-4 hallucinations. Introduced token governance and cost-control mechanisms with callbacks, prompt trimming, and budget capping. Deployed AKS with He

AI Engineer at Hearst

October 1, 2023 - July 31, 2024

Built Python (FastAPI, Celery, Redis) ETL pipelines to capture, process, and enrich financial transactions, trade logs, and voice data; persisted features in PostgreSQL and Cassandra for downstream risk analytics. Designed optimized SQL/time-series schemas with multi-region replication in Azure Database for PostgreSQL. Orchestrated real-time fraud/compliance detection with LangChain, embeddings, and GPT APIs to extract patterns, disclosures, and risk signals. Developed LangChain-based retrieval/classification layers for embeddings and Azure Cognitive Search vector retrieval; integrated dashboards in React, Grafana, and Power BI for near real-time transparency. Automated data validation with Pandas + PyTest; deployed on AKS, Azure Functions, and VM Scale Sets with zero-downtime CI/CD. Enhanced multilingual risk tagging via Whisper + TensorFlow, and embedded GPT-4 narrative summarization for management insights in dashboards. Used PyTorch + Hugging Face for classification/embedding of na

Machine Learning Engineer at Trans Union

September 1, 2019 - July 31, 2023

Project 1: Financial News & Credit Insights NLP Platform — Ingested financial filings, analyst reports, and earnings transcripts via Azure Data Factory/Functions; trained transformer-based models (BERT, RoBERTa, XLNet, Longformer) for NER, sentiment, and topic modeling with governance dashboards. Developed context-aware summarization using sequence-to-sequence architectures (T5, Pegasus) on redacted, compliance-approved datasets with groundings to verified indices in Azure Cognitive Search. Established governance via MLflow with reproducibility; addressed class imbalance with focal loss and domain lexicon augmentation; deployed inference on AKS with JWT RBAC and Key Vault; exported models to ONNX/TorchScript and optimized CPU performance with Azure Container Apps. Built blue-green/canary deployments gated by precision/recall/fairness gates; logged experiments in MLflow and Azure Blob Storage for immutable lineage. Implemented GDPR/CCPA controls (anonymization, TLS, KMS; retention; RB

Data Scientist at Arete IT Services

May 1, 2018 - July 31, 2019

Queried and retrieved large-scale patient datasets from Oracle DB; performed ETL to standardize formats for ML pipelines. Built feature engineering (PCA, scaling, comorbidity scoring) and validated models (Logistic Regression, SVM, Gradient Boosting, Random Forest) with cross-validation. Deployed models on AWS EC2 and Lambda for scalable inference; implemented automated preprocessing pipelines for consistent training-serving data. Created daily/monthly summary and benchmarking reports in Tableau; collaborated in Agile/Scrum to deliver production-ready ML solutions.