Akhil Sai Gudala

AI/ML Engineer at BNY Mellon

Architected a Retrieval-Augmented Generation (RAG) solution using LangChain, FAISS, and pgvector; developed FastAPI-based microservices exposing LLM agents to enterprise data; fine-tuned domain LLMs with LoRA/QLoRA; established real-time observability with Prometheus & Grafana; automated ML lifecycle with MLflow, Airflow, Docker, and Azure DevOps; integrated AI-powered insights into internal analytics dashboards; guided cross-functional teams on LLM deployment and MLOps best practices.

Data Engineer at McKinsey & Company

Led a real-time analytics platform using Kafka, Spark Streaming, and AWS Glue; implemented a dynamic surge-pricing engine with XGBoost and TensorFlow via Databricks MLflow; developed a RAG-based driver-recommendation system to optimize utilization; containerized AI services with FastAPI and Docker, enabling scalable inference via AWS Lambda; built automated MLOps pipelines with Airflow, MLflow, and GitHub Actions; implemented real-time anomaly detection with PySpark/SQL and migrated legacy ETL to AWS Databricks to reduce costs; collaborated with data science and product teams to infuse LLM insights into dashboards.

Associate Consultant / Data Engineer at Atos Syntel

Designed and deployed ML-powered data pipelines using AWS Glue, Redshift, S3, and Databricks; automated ETL workflows with Python and PySpark; built big data pipelines integrating transactional and behavioral datasets to empower pricing, demand forecasting, and market insights; developed and deployed predictive models in AWS SageMaker; created interactive dashboards with Tableau; implemented data quality, anomaly detection, and validation; optimized cloud storage and analytics on Redshift/S3; collaborated with cross-functional teams to deploy end-to-end AI/ML pipelines.