Saicharan Yatharla

Results-driven Generative AI & Data Engineer with 4+ years of experience designing enterprise-scale AI/ML pipelines, LLM-powered applications, RAG systems, and cloud data platforms. Expert in Retrieval-Augmented Generation (RAG), vector databases, LLM fine-tuning, agentic AI workflows, and embedding-based semantic search. Hands-on with LangChain, LlamaIndex, OpenAI APIs, AWS SageMaker, Azure Databricks, PySpark, dbt, and Snowflake.

Delivered production GenAI solutions for anomaly detection, NLP classification, and intelligent data products across finance, manufacturing, and EdTech sectors.

Generative AI & Data Engineer - Oaktree Capital Management - Los Angeles, CA

(2024-07)

Led GenAI and cloud data engineering for a global investment management firm — built RAG-powered analytics pipelines, LLM-integrated data products, anomaly detection systems, and modernised petabyte-scale AWS infrastructure.

• Designed and deployed end-to-end RAG pipelines integrating vector databases and embedding models to build intelligent document search and Q&A systems over investment datasets.
• Built Agentic AI workflows using LangChain and AWS SageMaker to automate multi-step data retrieval, summarization, and decision-support tasks across investment platforms.
• Implemented LLM-integrated data pipelines (Python, PySpark, dbt) to enrich structured financial datasets with AI-generated insights, classifications, and anomaly flags.
• Engineered semantic search solutions using vector embeddings and chunking strategies enabling natural language querying over petabyte-scale datasets in S3 and Redshift.
• Delivered ML-powered anomaly detection and predictive analytics (NLP, LSTM, SageMaker, Kubeflow) for real-time security KPI monitoring and performance forecasting.
• Built layered dbt models (staging to intermediate to marts) with Jinja macros and SCD Type 2 logic supporting AI-ready dimensional data marts for claims, providers, and encounters.
• Designed scalable ETL pipelines (AWS Glue, Redshift, PySpark); automated incremental loads with Apache Airflow; built serverless file processing with AWS Lambda.
• Enforced HIPAA and PCI-DSS compliance through Terraform-managed IAM roles, encryption at rest and in transit, and fully automated CI/CD via CodePipeline.
• Deployed Denodo data virtualization to unify structured and unstructured sources for AI/ML workloads; designed microservices for SaaS AI data products using Flask and Django.

Data Engineer - InMobi - Bangalore

(2021-03 - 2022-06)

Built distributed data solutions on Hadoop and AWS supporting ML model training, real-time streaming analytics, and cloud data infrastructure for manufacturing intelligence.

• Built and deployed ML models on AWS SageMaker for predictive analytics; developed in-time peak/valley alert monitoring using Python, SQL, and threshold-based auto-email triggers.
• Architected real-time streaming pipelines using AWS Kinesis Data Streams, Firehose, and Lambda to capture and store event data in S3 and DynamoDB for ML training datasets.
• Designed Hadoop-based distributed ETL solutions (HDFS, HIVE, Sqoop, Kinesis) and Spark/Kafka/HBase stacks for scalable feature engineering pipelines.
• Built CI/CD pipelines using Docker, Jenkins, and AWS ECS; used Terraform Cloud with S3 and Lambda for infrastructure deployment and EMR cluster management.
• Integrated Snowflake with S3 for nested JSON ingestion using Clone and Time Travel; built data quality and compliance checks using Airflow, SQL, and Cloud Functions.
• Followed Agile/SAFe delivery with Jira; tracked team velocity and sprint progress within Program Increment (PI) planning cycles.

Data Analyst / SQL Developer - AudLink - Bangalore, India

(2019-03 - 2021-03)

Delivered BI reporting, data warehousing, ETL development, and early ML prototyping for a quality and compliance-focused organization.

• Built ML algorithm prototypes using Python (Pandas, NumPy, Matplotlib) and R for predictive modeling and statistical analysis supporting business decision-making.
• Designed Power BI dashboards (bar, waterfall, gauge, tree map) with tabular cube models and data quality validation; built SSIS ETL packages using Lookup, SCD, Merge Join, and Pivot transformations.
• Developed conceptual, logical, and physical data models in Erwin for OLTP and reporting systems; administered and optimized SQL Server RDBMS production environments.

Master of Science - Data Science & Information Systems - Wilmington University (2022-08 - 2024-04)

Bachelor of Science - Computer Science & Engineering - Hyderabad Institute of Technology and Management (2015-04 - 2019-06)