GenAI Engineer at U.S. Bank

Led the development of LLM-powered embeddings to model semantic product relationships, improving search accuracy and enabling cross-sell recommendations. Built GPT-3 based summarization to analyze unstructured feedback from reviews, tickets, and chats. Implemented LSTM-based forecasting in TensorFlow to predict churn, purchase probability, and browsing behavior. Processed multi-channel data with PySpark for near real-time analytics. Designed a personalization framework combining LLM outputs with user interaction features to deliver dynamic recommendations and personalized experiences. Deployed low-latency inference services on AWS Lambda and containerized AI workloads with Docker and Kubernetes. Implemented an event-driven Kafka pipeline for millisecond-scale streaming of behavioral and transactional data. Automated weekly model retraining with AWS Step Functions and CloudWatch. Collaborated with marketing to generate GPT-3-based personalized campaigns and created dashboards in Amazon

Sr Python AI Engineer at M&T Bank

Partnered with product managers and application teams to analyze ADAS features, sensor data streams, and functional requirements for advanced driver-assistance systems. Processed real-time sensor data (RADAR, LIDAR, cameras) to validate and enhance ADAS functionalities through advanced analytics. Implemented Generative AI-powered pipelines leveraging LLMs for ADAS core features (ACC, APA, BSM, AEB). Built NLP-based real-time solutions for image classification, object detection, and semantic segmentation using PyTorch. Designed a Retrieval-Augmented Generation (RAG) pipeline enabling voice-command intent recognition and context-aware responses by integrating external knowledge bases. Fine-tuned Generative AI models with RLHF and PEFT techniques to optimize ADAS-related responses and decision-making. Created microservices-based simulation modules and a Digital Testing Platform (DTP) on AWS with NVIDIA GPU containers. Built scalable GenAI workflows on GCP (Vertex AI, BigQuery, GKE). Devel

Sr. Python Developer at Zurich North America

Understand scope? Led Python cloud applications using AWS services (Lambda, S3, EMR) and PostgreSQL; built Full Stack applications with Django and React; performed large-scale data warehousing with Redshift; developed REST APIs with FastAPI/Flask; deployed microservices with Docker/Kubernetes (EKS); implemented Infrastructure as Code (IaC) using AWS CDK and CloudFormation; configured GPU-optimized EC2 instances for EKS; automated simulation triggers via Lambda, API Gateway, MWAA, S3, and boto3; orchestrated large-scale PySpark ETL with AWS Glue; designed React-based UIs for simulation job configuration and results visualization; built data pipelines on GCP (Vertex AI, BigQuery, GKE); used SQLAlchemy and Alembic for migrations; created Airflow DAGs and Python operators; established CI/CD pipelines with Git, Jenkins, and Ansible; wrote tests with pytest/unittest; participated in Agile ceremonies.

Python developer at Costco Wholesale

Developed SIS (Site Information Service) and ETB (Enterprise the Business) applications using Python and Flask to track information across multiple sites. Built dynamic web pages with Flask WTForms; implemented RESTful APIs with Flask; designed SQLAlchemy ORM models and managed migrations with Alembic. Used MySQL as the primary database; integrated Google Maps API with Geocoder; ingested data from APIs and file systems; processed large datasets with Pandas and NumPy; developed PySpark ETL for large-scale CSV processing; created AWS Lambda functions and Step Functions for serverless workflows; built reusable AWS Glue wrappers; established CI/CD pipelines with Git, GitHub, Jenkins, and Ansible; containerized with Docker and Kubernetes; authored unit/integration tests with pytest/unittest; mentored interns.