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I’m a Senior Data Scientist and AI/ML professional with 11+ years of experience building production-grade machine learning and Generative AI solutions across cloud platforms like Azure and AWS. I specialize in end-to-end RAG pipelines and enterprise knowledge assistants—covering document ingestion, chunking, embeddings, vector search, reranking, and grounded response generation to improve relevance while reducing hallucinations. Beyond RAG, I build agentic AI and conversational systems using LLM tool/function calling and orchestration patterns, along with predictive and analytical ML models for forecasting, classification, anomaly detection, and decision support. I enjoy translating complex business requirements into scalable Python services (FastAPI/Flask) with strong MLOps practices, rigorous evaluation, and deployment pipelines that are reliable in real-world environments.…I’m a Senior Data Scientist and AI/ML professional with 11+ years of experience building production-grade machine learning and Generative AI solutions across cloud platforms like Azure and AWS. I specialize in end-to-end RAG pipelines and enterprise knowledge assistants—covering document ingestion, chunking, embeddings, vector search, reranking, and grounded response generation to improve relevance while reducing hallucinations. Beyond RAG, I build agentic AI and conversational systems using LLM tool/function calling and orchestration patterns, along with predictive and analytical ML models for forecasting, classification, anomaly detection, and decision support. I enjoy translating complex business requirements into scalable Python services (FastAPI/Flask) with strong MLOps practices, rigorous evaluation, and deployment pipelines that are reliable in real-world environments.

Hruthik Gonuguntla

Data Scientist, AI Engineer, Software Engineer, +4

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I’m a Senior Data Scientist and AI/ML professional with 11+ years of experience building production-grade machine learning and Generative AI solutions across cloud platforms like Azure and AWS. I specialize in end-to-end RAG pipelines and enterprise knowledge assistants—covering document ingestion, chunking, embeddings, vector search, reranking, and grounded response generation to improve relevance while reducing hallucinations. Beyond RAG, I build agentic AI and conversational systems using LLM tool/function calling and orchestration patterns, along with predictive and analytical ML models for forecasting, classification, anomaly detection, and decision support. I enjoy translating complex business requirements into scalable Python services (FastAPI/Flask) with strong MLOps practices, rigorous evaluation, and deployment pipelines that are reliable in real-world environments.…I’m a Senior Data Scientist and AI/ML professional with 11+ years of experience building production-grade machine learning and Generative AI solutions across cloud platforms like Azure and AWS. I specialize in end-to-end RAG pipelines and enterprise knowledge assistants—covering document ingestion, chunking, embeddings, vector search, reranking, and grounded response generation to improve relevance while reducing hallucinations. Beyond RAG, I build agentic AI and conversational systems using LLM tool/function calling and orchestration patterns, along with predictive and analytical ML models for forecasting, classification, anomaly detection, and decision support. I enjoy translating complex business requirements into scalable Python services (FastAPI/Flask) with strong MLOps practices, rigorous evaluation, and deployment pipelines that are reliable in real-world environments.

Available to hire

I’m a Senior Data Scientist and AI/ML professional with 11+ years of experience building production-grade machine learning and Generative AI solutions across cloud platforms like Azure and AWS. I specialize in end-to-end RAG pipelines and enterprise knowledge assistants—covering document ingestion, chunking, embeddings, vector search, reranking, and grounded response generation to improve relevance while reducing hallucinations.

Beyond RAG, I build agentic AI and conversational systems using LLM tool/function calling and orchestration patterns, along with predictive and analytical ML models for forecasting, classification, anomaly detection, and decision support. I enjoy translating complex business requirements into scalable Python services (FastAPI/Flask) with strong MLOps practices, rigorous evaluation, and deployment pipelines that are reliable in real-world environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Advanced

Work Experience

Senior Data Scientist at Blue Cross Blue Shield

July 1, 2023 - Present

Designed and implemented enterprise-scale AI/ML and Generative AI solutions leveraging RAG, MCP-enabled architectures, agentic AI, LLMs, NLP, and Transformers in AWS environments. Architected end-to-end RAG pipelines with ingestion, chunking, metadata extraction, embeddings, vector indexing, semantic retrieval, reranking, contextual prompting, and grounded response generation. Built AI agents and chatbots using multi-step reasoning, tool calling/function invocation, planning, memory, and orchestration patterns. Developed NLP pipelines for healthcare text preprocessing and analysis, and built scalable semantic search and knowledge-retrieval architectures using embeddings and vector databases (e.g., FAISS). Implemented GenAI automation for summarization, extraction, classification, QA, and knowledge discovery, and optimized inference and retrieval quality with evaluation frameworks. Exposed ML/LLM capabilities through secure REST APIs (FastAPI/Flask), integrated with enterprise systems,

Senior Data Scientist at Blue Cross Blue Shield, CA

July 1, 2023 - Present

Designed and implemented enterprise-scale AI/ML and Generative AI solutions leveraging RAG, MCP-enabled architectures, agentic AI, NLP/Transformers, and LLMs on AWS. Built end-to-end RAG pipelines for ingestion, chunking, metadata extraction, embeddings, vector indexing, retrieval, reranking, contextual prompting, and grounded response generation. Developed tool-using AI agents for multi-step workflows, planning, memory, and orchestration with secure tool calling. Created member-facing conversational AI and chatbot backends via REST services. Engineered semantic search and knowledge-retrieval systems using embeddings, FAISS/vector DBs, and evaluation frameworks to reduce hallucinations and improve answer relevance. Built LLM-powered document intelligence workflows (summarization, extraction, classification, QA) and implemented model optimization and systematic evaluation using precision/recall, F1, AUC-ROC, and retrieval/grounding metrics. Delivered scalable Python APIs with FastAPI/Fl

Data Scientist at State of California

May 1, 2021 - June 30, 2023

Developed enterprise AI and ML solutions on Azure combining NLP, LLMs, intelligent search, conversational AI, deep learning, and predictive modeling. Built chatbots and knowledge-search applications using intent classification, entity extraction, dialogue management, contextual embeddings, and retrieval-based techniques. Designed intelligent search and navigation strategies using heuristic and pathfinding algorithms (A*, BFS, DFS, etc.) alongside semantic similarity and ranking. Built Transformer-based NLP pipelines for classification, semantic similarity, question answering, and summarization. Implemented embedding and semantic-search pipelines using vector indexing for context-aware retrieval across large unstructured datasets. Delivered ML-ready datasets using PySpark/SQL, deployed model-serving APIs with FastAPI/Flask, and improved reliability through systematic evaluation (AUC-ROC, precision/recall, F1, cross-validation).

Data Scientist at State of California, CA

May 1, 2021 - June 30, 2023

Built enterprise AI and machine learning solutions on Azure, including intelligent search, conversational AI/chatbots, NLP pipelines, and predictive modeling. Implemented chatbot systems using intent classification, entity extraction, dialogue management, contextual embeddings, and retrieval-based approaches. Designed search strategies using BFS/DFS/A* and heuristic pathfinding combined with semantic similarity and ranking. Developed Transformer-based pipelines for classification, semantic similarity, question answering, summarization, and information retrieval. Applied RLHF concepts to improve language model behavior with preference/reward modeling and iterative refinement. Created embedding and semantic-search pipelines with vector indexing and knowledge discovery. Developed deep learning models (PyTorch/TensorFlow) and supervised/unsupervised ML using scikit-learn/XGBoost/RF/clustering. Built Azure ML and data workflows (Synapse, ADLS, ADF) and REST model-serving APIs using FastAPI/

AI Engineer at Citi Bank

September 1, 2018 - April 30, 2021

Built an enterprise AI platform for conversational AI, ML, NLP, deep learning, and intelligent automation for retail/commercial banking. Developed chatbot back-end services with conversational intent/entity handling, dialogue management, context maintenance, and REST integrations for account/transaction-related requests. Created NLP pipelines using NLTK, TF-IDF, Word2Vec, and Hugging Face Transformers for text preprocessing, entity extraction, classification, and semantic similarity. Implemented BERT-based classification models and scalable inference workflows with batching/GPU optimizations. Developed reusable Scikit-learn training pipelines (logistic regression, random forest, gradient boosting, SVM) with hyperparameter tuning and consistent preprocessing via FeatureUnion/custom transformers. Built deep learning pipelines using transfer learning (xResNet50) for document classification (checks/ID), reducing manual review errors and improving processing efficiency. Exposed models throu

AI Engineer at Citi Bank, NY

September 1, 2018 - April 30, 2021

Developed an enterprise AI platform supporting conversational AI, ML, NLP, deep learning, and intelligent automation for retail/commercial banking. Built chatbot conversational backends with Flask/FastAPI and REST APIs to interpret banking inquiries, extract entities/intent, manage conversational context, and respond via integrated services. Implemented NLP pipelines using NLTK, TF-IDF, Word2Vec, and Hugging Face Transformers for classification and semantic similarity over finance/compliance text. Fine-tuned BERT-style models for sentiment, intent detection, and categorization. Created reusable ML training pipelines using scikit-learn with cross-validation and hyperparameter search (GridSearchCV/RandomizedSearchCV). Built deep learning computer-vision pipelines using PyTorch and xResNet50 with transfer learning for check/ID document classification and reduced manual review errors. Built high-volume (50M+) sentiment/trend analysis pipelines using BERT-based contextual classification and

Software Engineer at Pfizer

July 1, 2016 - August 31, 2018

Worked on server-side Python development, REST/API design, database-driven application workflows, and automation solutions. Built modular reusable Python packages to standardize development practices and improve maintainability. Implemented RESTful web services and integrations with external/internal systems via REST, SOAP, file interfaces, and database connectors. Designed and optimized relational database structures, stored procedures/views/triggers, and SQL queries using SQL Server, Oracle, and DB2 for transactional and reporting workloads. Collaborated with business analysts, DBA teams, and QA to deliver enhancements. Supported development lifecycle activities including testing and Agile/Scrum coordination.

Python Developer at MetLife

February 1, 2014 - June 30, 2016

Developed scalable full-stack web applications using Python, Django, and JavaScript, with API-driven architectures. Built and maintained back-end applications using Django and Django REST Framework, and designed RESTful APIs with DRF and FastAPI. Implemented high-performance backend microservices with FastAPI, including validation, authentication/authorization, exception handling, and asynchronous processing. Optimized database interactions using ORMs (Django ORM/SQLAlchemy) and performance-focused SQL/stored procedures across relational databases (PostgreSQL, MySQL, Oracle, SQL Server). Implemented secure auth (RBAC, session management), reusable Python modules for validation/error handling/logging, and automated testing strategies. Supported deployments and maintenance using Linux, Git, Jenkins/CI-CD, and web servers (Apache/Nginx).

Software Engineer at Pfizer, NY

February 1, 2014 - June 30, 2016

Worked on backend development and enterprise integration using Python, SQL, and enterprise frameworks. Built server-side business logic and reusable components to support critical operations. Designed and developed RESTful APIs and services for communication between internal systems and external third-party platforms. Implemented modular Python packages to standardize practices and improve maintainability. Built backend services using Flask and Django with authentication/session management and workflow capabilities. Designed relational database structures (SQL Server/Oracle/DB2) with stored procedures/views/triggers for high-volume transactional and regulatory reporting. Integrated systems via REST, SOAP, and file-based interfaces to ensure reliable data synchronization. Collaborated with analysts/DBAs/QA to resolve technical issues and deliver enhancements in Agile/Scrum environments.

Python Developer at MetLife, NY

February 1, 2014 - June 30, 2016

Developed scalable full-stack enterprise applications using Python, Django, and JavaScript frameworks. Built backend services with Django/DRF and FastAPI, creating reusable components and robust API-driven architectures. Implemented RESTful APIs for integration with frontends and third-party systems. Built modular backend microservices with FastAPI/FastAPI-style asynchronous endpoints, validation, authentication, and exception handling. Worked on frontend components (HTML/CSS/JS, jQuery, Bootstrap, AngularJS). Integrated internal/external APIs for policy administration, claims intake, and underwriting automation. Optimized ORM/database interactions and wrote complex SQL, stored procedures, and performance improvements on relational databases. Added secure authentication/authorization with RBAC and API security practices. Implemented testing strategies and supported CI/CD and production deployment on Linux with web servers and cloud hosting.