artificial intellegence engineer

Puneeth Naidu

+1-773-***-**** *********************@*****.*** LinkedIn GitHub

Summary

AI/ML Engineer with 3+ years of experience building machine learning, Generative AI, and data-driven applications across financial services and enterprise platforms. Experienced in developing RAG pipelines, semantic search solutions, recommendation systems, and AI-powered automation workflows using Python, FastAPI, LangChain, and AWS. Skilled in model development, API design, cloud deployment, and translating business requirements into scalable AI solutions

Technical Skills

Category

Skills

Programming

Python, SQL, PySpark

Machine Learning & Frameworks

Scikit-learn, TensorFlow, PyTorch, XGBoost

Generative AI & LLMs

LangChain, RAG, Prompt Engineering, LLM Applications

Cloud Platforms

AWS, Docker, FastAPI, REST APIs, Model Deployment, CI/CD

Data Processing & Analytics

Pandas, NumPy, PySpark

MLOps & Deployment

MLflow, Docker, Kubernetes, CI/CD, Model Monitoring

Streaming & Data

Kafka, ETL Pipelines, NoSQL

APIs & Integration

FastAPI, Flask, REST APIs

Visualization

Tableau, Power BI

Tools & Others

Git, Linux, SHAP, LIME, Jupyter

Education

DePaul University Master of Science, Computer Science

Work Experience

Fiserv AI/ML Engineer Aug 2025 – Present

Developed Generative AI solutions using Python, FastAPI, and Large Language Models (LLMs) to automate document-processing workflows and improve operational efficiency.

Designed and implemented Retrieval-Augmented Generation (RAG) workflows using LangChain, embeddings, and semantic search techniques to improve enterprise document retrieval and reduce manual information discovery effort.

Built and deployed REST APIs supporting AI-powered document analysis, semantic search, and conversational AI applications.

Leveraged AWS services including Bedrock, Lambda, and S3 along with Docker containers to deploy scalable AI applications in cloud environments.

Evaluated prompt engineering, prompt chaining, and context-management strategies to improve response relevance and reduce hallucinations in LLM-powered applications.

Collaborated with business stakeholders to gather requirements, define success criteria, and deliver production-ready AI solutions aligned with business objectives.

Performed model evaluation, response-quality assessment, and performance monitoring to continuously improve AI application reliability.

Utilized MLflow-based experiment tracking and Git-driven CI/CD workflows to support model evaluation, deployment automation, and application maintenance.

Environment: Python, FastAPI, LangChain, LLMs, RAG, AWS (Bedrock, Lambda, S3), Docker, PostgreSQL, MLflow, Git, REST APIs, Linux

Intercontinental Exchange (ICE) AI/ML Engineer Intern Aug 2024 – Jun 2025

Developed machine learning and Generative AI solutions supporting intelligent automation and enterprise data-processing initiatives.

Built document-intelligence workflows using NLP, embeddings, vector search, and LLM-based information extraction techniques.

Developed backend services and REST APIs using FastAPI and Python for AI-driven applications and automation workflows.

Contributed to the design and evaluation of recommendation systems and semantic search solutions using FAISS and retrieval-based architectures.

Conducted model validation, benchmarking, and performance analysis to improve prediction accuracy and retrieval effectiveness.

Developed data pipelines for preprocessing, feature engineering, and machine learning model training activities.

Applied SHAP and LIME techniques to improve model interpretability and support transparent evaluation of machine learning predictions.

Collaborated with cross-functional teams in Agile environments to deliver AI features, enhancements, and production support.

Environment: Python, FastAPI, Scikit-learn, LangChain, FAISS, SQL, Pandas, NumPy, SHAP, LIME, Git

Birlasoft Software Engineer Jul 2022 – Aug 2023

Developed and maintained enterprise web applications using Python, SQL, and REST APIs supporting business-critical operations.

Designed backend services and data-processing modules to improve application reliability and support enterprise workflows.

Optimized SQL queries, stored procedures, and validation processes to improve data quality and application performance.

Developed reusable REST APIs and integrated third-party services to support enterprise system interoperability.

Automated reporting and data-analysis workflows using Python and SQL, reducing manual effort and improving reporting efficiency.

Integrated backend services with Kafka-based messaging workflows to support asynchronous processing and reliable system communication.

Participated in Agile/Scrum activities including sprint planning, code reviews, release support, and production issue resolution.

Worked closely with QA teams, developers, and business stakeholders to troubleshoot defects and improve overall application performance.

Environment: Python, SQL, REST APIs, PostgreSQL, MySQL, Kafka, Git, Linux

Chicago, Illinois Jun 2025

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