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I am Puneet Anurag Pidaparthy, an AI-driven Full Stack Engineer focused on building scalable web platforms and ML-powered systems. I design and ship AI-enabled dashboards and services, combining React.js, Flask, FastAPI, and cloud-native deployments to deliver real-time insights and automated predictions. I value performance, reliability, and user-centric design in every project.\n\nAcross roles at VINYO CA, Cognizant, Dell Technologies, and Trinity Technologies, I have owned end-to-end ML pipelines, CI/CD automation, and team mentoring, emphasizing performance optimization, secure data practices, and collaborative problem-solving. I enjoy turning complex challenges into deployable, maintainable solutions and guiding colleagues to adopt best practices in Python, containerization, and data engineering.…I am Puneet Anurag Pidaparthy, an AI-driven Full Stack Engineer focused on building scalable web platforms and ML-powered systems. I design and ship AI-enabled dashboards and services, combining React.js, Flask, FastAPI, and cloud-native deployments to deliver real-time insights and automated predictions. I value performance, reliability, and user-centric design in every project.\n\nAcross roles at VINYO CA, Cognizant, Dell Technologies, and Trinity Technologies, I have owned end-to-end ML pipelines, CI/CD automation, and team mentoring, emphasizing performance optimization, secure data practices, and collaborative problem-solving. I enjoy turning complex challenges into deployable, maintainable solutions and guiding colleagues to adopt best practices in Python, containerization, and data engineering.

Puneet Anurag Pidaparthy

Full Stack Developer, Back-End Developer, Front-End Developer, +4

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I am Puneet Anurag Pidaparthy, an AI-driven Full Stack Engineer focused on building scalable web platforms and ML-powered systems. I design and ship AI-enabled dashboards and services, combining React.js, Flask, FastAPI, and cloud-native deployments to deliver real-time insights and automated predictions. I value performance, reliability, and user-centric design in every project.\n\nAcross roles at VINYO CA, Cognizant, Dell Technologies, and Trinity Technologies, I have owned end-to-end ML pipelines, CI/CD automation, and team mentoring, emphasizing performance optimization, secure data practices, and collaborative problem-solving. I enjoy turning complex challenges into deployable, maintainable solutions and guiding colleagues to adopt best practices in Python, containerization, and data engineering.…I am Puneet Anurag Pidaparthy, an AI-driven Full Stack Engineer focused on building scalable web platforms and ML-powered systems. I design and ship AI-enabled dashboards and services, combining React.js, Flask, FastAPI, and cloud-native deployments to deliver real-time insights and automated predictions. I value performance, reliability, and user-centric design in every project.\n\nAcross roles at VINYO CA, Cognizant, Dell Technologies, and Trinity Technologies, I have owned end-to-end ML pipelines, CI/CD automation, and team mentoring, emphasizing performance optimization, secure data practices, and collaborative problem-solving. I enjoy turning complex challenges into deployable, maintainable solutions and guiding colleagues to adopt best practices in Python, containerization, and data engineering.

Available to hire

I am Puneet Anurag Pidaparthy, an AI-driven Full Stack Engineer focused on building scalable web platforms and ML-powered systems. I design and ship AI-enabled dashboards and services, combining React.js, Flask, FastAPI, and cloud-native deployments to deliver real-time insights and automated predictions. I value performance, reliability, and user-centric design in every project.\n\nAcross roles at VINYO CA, Cognizant, Dell Technologies, and Trinity Technologies, I have owned end-to-end ML pipelines, CI/CD automation, and team mentoring, emphasizing performance optimization, secure data practices, and collaborative problem-solving. I enjoy turning complex challenges into deployable, maintainable solutions and guiding colleagues to adopt best practices in Python, containerization, and data engineering.

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Work Experience

Full Stack Developer at Uber

January 1, 2025 - Present

Designed Python backend services using FastAPI and gRPC to handle rider and driver workflow requests, processing 600K–800K trip and status records per day through real-time endpoints and scheduled batch jobs.

Full Stack Python Developer at Cognizant

August 1, 2022 - December 31, 2022

Developed Python backend services using Flask and REST APIs to validate and process data from internal applications and scheduled feeds, handling 40K–60K records per day for downstream systems. Implemented Python-based data handling logic for request validation, error handling, and response formatting, integrating backend services with PostgreSQL and MySQL across 20+ relational tables. Coordinated with backend, frontend, and QA teams during sprint cycles to clarify requirements and review Python code changes.

Full Stack Python Developer at Dell Technologies

July 1, 2020 - August 31, 2022

Engineered Python backend services using FastAPI and Flask to support licensing and entitlement workflows, handling 70K–100K service requests per day from internal sales and fulfillment platforms. Implemented Python batch jobs to reconcile license activation and usage data from 6–8 internal source systems, running on daily and weekly schedules and writing validated results to relational databases used by downstream reporting. Designed REST endpoints consumed by internal web interfaces built with React.js, supporting 20–25 business users during daily operational reviews. Constructed relational schemas and SQL queries using PostgreSQL and MySQL to support license, entitlement, and workflow data across 30+ tables. Integrated Python services with a small number of Java-based enterprise apps via REST to exchange order, customer, and entitlement records, maintaining data consistency across multiple backend systems. Deployed Python applications using Docker into Kubernetes (OpenShift) e

AI Software Engineer at VINYO CA

January 1, 2025 - Present

Engineered AI-integrated web dashboards combining React.js, Flask, and AWS Lambda for real-time analytics and automated predictions. Designed RESTful APIs with Flask and FastAPI for ML model inference and data ingestion; implemented JWT-based authentication for secure data exchange. Deployed ML microservices (classification, image compression, and alerting) using AWS Lambda, SageMaker, and Docker, enabling automated retraining pipelines. Implemented Redis Pub/Sub and WebSocket channels for real-time prediction updates and event streaming across dashboards. Automated builds, testing, and model deployment triggers using GitHub Actions, cutting CI/CD time by 40%. Utilized CloudWatch and Slack alerts to monitor inference latency, server uptime, and ML service drift. Mentored junior developers in Python best practices, Dockerization, and data pipeline automation for ML workflows.

Full Stack Python Developer at DELL TECHNOLOGIES

January 1, 2021 - August 31, 2022

Designed ETL and ML pipelines using Pandas, Flask, and Celery to process, train, and deploy predictive models. Integrated Snowflake and PostgreSQL for analytics workflows; optimized data ingestion for model training jobs. Developed microservices for data preprocessing, model inference, and logging using Flask and Django. Automated background ML workflows with Celery-Redis for retraining and hyperparameter tuning. Containerized and deployed models with Jenkins pipelines and AWS EC2/Docker, implementing auto-scaling policies. Configured AWS CloudWatch and health scripts to track ML job failures, retraining frequency, and accuracy drift. Authored onboarding documentation for data pipeline setup, feature engineering, and CI/CD integration.

Python Developer Intern at TRINITY TECHNOLOGIES

July 1, 2020 - January 31, 2021

Built real-time IoT ingestion pipelines using Apache Kafka, Hudi, and AWS Lake Formation for telemetry data analytics. Assisted in ML-ready data lakehouse design using Apache Iceberg and AWS S3 to unify structured and unstructured sources. Integrated Prometheus, Loki, and Grafana dashboards for anomaly detection and model inference performance tracking. Automated metadata extraction and incremental updates for training datasets using Python and PostgreSQL. Implemented PyTest-based unit tests and documentation for ingestion and model deployment scripts.