Senior AI/ML engineer with 9+ years of experience delivering enterprise AI/ML solutions across banking, healthcare, insurance, financial services, and analytics. Strong track record building production-grade Generative AI and Agentic AI systems, RAG pipelines, and scalable microservices. Hands-on across the ML lifecycle—from data ingestion and feature engineering to model training, evaluation, deployment, monitoring, and production support—using Python, SQL, FastAPI, Spark/Databricks, AWS/Azure/GCP, and MLflow.…

Satya Keerthi Dara

Senior AI/ML engineer with 9+ years of experience delivering enterprise AI/ML solutions across banking, healthcare, insurance, financial services, and analytics. Strong track record building production-grade Generative AI and Agentic AI systems, RAG pipelines, and scalable microservices. Hands-on across the ML lifecycle—from data ingestion and feature engineering to model training, evaluation, deployment, monitoring, and production support—using Python, SQL, FastAPI, Spark/Databricks, AWS/Azure/GCP, and MLflow.…

Available to hire

Senior AI/ML engineer with 9+ years of experience delivering enterprise AI/ML solutions across banking, healthcare, insurance, financial services, and analytics. Strong track record building production-grade Generative AI and Agentic AI systems, RAG pipelines, and scalable microservices.

Hands-on across the ML lifecycle—from data ingestion and feature engineering to model training, evaluation, deployment, monitoring, and production support—using Python, SQL, FastAPI, Spark/Databricks, AWS/Azure/GCP, and MLflow.

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Skills

Experience Level

Work Experience

AI/ML Engineer at US Bank
July 1, 2025 - Present
Architected enterprise Generative AI and Agentic AI services using Python, FastAPI, LangChain, LangGraph, LlamaIndex, LLMs, RAG, embeddings, and vector search for banking knowledge and workflow automation. Designed multi-step agent workflows including planning, tool invocation, retrieval, state management, memory, validation, human-in-the-loop controls, exception handling, and guardrails. Built advanced RAG pipelines with document ingestion, chunking, metadata filtering, semantic and hybrid retrieval, contextual grounding, and source-aware response generation. Developed backend microservices and reusable APIs for agent orchestration, retrieval, response validation, tool execution, and workflow status/persistence, integrating PostgreSQL, Redis, and vector databases. Implemented evaluation workflows for relevance/groundedness/citation quality/latency/reliability and established structured testing for API and end-to-end workflows. Containerized services with Docker and deployed via Kubern
AI/ML Engineer at CVS - Deerfield, Illinois
February 1, 2023 - June 30, 2025
Designed and deployed enterprise healthcare knowledge retrieval and AI platform services for document intelligence, semantic search, workflow automation, and business-user assistance. Built production-ready RAG architectures for ingestion, parsing, chunking, metadata enrichment, access filtering, retrieval, reranking, and contextual grounding. Developed scalable ingestion workflows for structured and unstructured healthcare documents and data, processing large datasets with Apache Spark and Databricks and preparing model-ready inputs. Built FastAPI/REST APIs for AI/search/document processing and model inference, with modular layers for ingestion, transformation, indexing, retrieval, orchestration, model interaction, APIs, and presentation. Integrated Pinecone, FAISS, and ChromaDB for vector storage and similarity search. Implemented validation/quality rules and evaluation workflows for retrieval accuracy, response relevance, groundedness, latency, reliability, and production performanc
ML Engineer at Morgan Stanley - Columbia, SC
January 1, 2021 - January 31, 2023
Built financial analytics and machine learning platform services using Python, FastAPI, Apache Spark, Databricks, SQL, and AWS. Delivered end-to-end ML pipelines covering ingestion, cleansing, transformation/validation, feature engineering, model training, evaluation, deployment, and monitoring. Created reusable data components for extraction/aggregation/reconciliation/transformations and model-ready feature generation. Developed predictive models with scikit-learn, TensorFlow, and PyTorch and exposed predictions via FastAPI REST APIs and microservices with production-grade validation, exception handling, retries, structured logging, and response controls. Used MLflow for experiment tracking, registration, versioning, and reproducibility. Containerized training/inference services with Docker and supported scalable deployment using Kubernetes; implemented CI/CD pipelines and testing (unit/integration/API). Monitored model performance, drift, service reliability, API latency, and product
ML Engineer/Data Scientist at Cigna - Scottsdale, Arizona
October 1, 2018 - December 31, 2020
Developed production-focused ML solutions for health insurance fraud detection, risk analytics, anomaly detection, and document intelligence. Built Python/SQL data pipelines processing claims, policy, provider, risk, and document/text data; implemented ingestion/cleansing/transformation/validation and feature-generation workflows for structured and unstructured inputs. Conducted exploratory analysis using Pandas/NumPy and statistical methods to identify patterns, gaps, outliers, and risk indicators. Engineered features from claims, policies, provider activity, and document content. Developed fraud detection/classification and anomaly detection models using scikit-learn, TensorFlow, PyTorch, and statistical techniques. Implemented NLP and information-extraction workflows for document classification, text processing, and entity extraction; performed model selection, tuning, cross-validation, thresholding, explainability, and evaluation. Built Flask REST APIs for model serving and integra
Data Scientist at Cognizant - Hyderabad, India
December 1, 2016 - May 31, 2018
Delivered enterprise forecasting and business analytics solutions including forecasting, classification, segmentation, and reporting using Python and SQL. Built reusable data-processing pipelines for collection, cleansing, transformation, validation, and preparation of structured data for analytics and model development. Performed EDA using Pandas/NumPy and statistical analysis to identify trends, patterns, outliers, and data-quality issues. Created model-ready datasets via feature engineering, missing-value handling, normalization, categorical encoding, and input validation. Developed forecasting and predictive models using scikit-learn, TensorFlow, PyTorch, and XGBoost along with regression/classification/statistical techniques. Designed workflows for recurring predictions, performance validation, and analytical reporting. Evaluated models with appropriate accuracy and business-focused checks. Built modular analytics applications and delivered Tableau/Power BI dashboards for KPIs, tr

Education

Bachelor of Technology – Computer Science at Jawaharlal Nehru Technological University
January 11, 2030 - August 6, 2026

Qualifications

Add your qualifications or awards here.

Industry Experience

Financial Services, Healthcare, Professional Services, Other

Skills

Experience Level