Sai Srujana R.
Artificial Intelligence Engineer @State Street
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WORK HISTORY
Artificial Intelligence Engineer @State Street
US
Architected and deployed a GPT-4 + LangChain-powered GenAI assistant to automate financial analysis, compliance summaries, and portfolio insights—cutting reporting time by 60%.• Implemented and optimized RAG pipelines with Pinecone + LlamaIndex for document retrieval, contextual summarization, and Q&A over 50K+ financial/regulatory records.• Designed and orchestrated semantic search pipelines and NLP-driven Q&A systems using FAISS, ChromaDB, and Azure Cognitive Search, delivering less than 1s latency.• Deployed and scaled LLM inference services with FastAPI, Docker, AKS, while automating CI/CD through GitHub Actions and Azure DevOps.• Optimized NLP outputs with RLHF-style personalization using Bandit Algorithms, improving response relevance by 28%.• Engineered and trained LSTM-based forecasting and CNN + NER models, while developing automated ETL & feature pipelines with Airflow, dbt, Delta Lake on Azure Databricks, reducing compliance workload by 50% and ensuring production-ready datasets.• Established and maintained real-time monitoring with Prometheus, Grafana, and Weights & Biases, enabling proactive drift detection and performance tracking.
EDUCATION
California State University, Fullerton
Master's degree, Information Systems, business analytics
Bhojreddy engineering college for women
Bachelor of Technology - BTech, Electrical, Electronic and Communications Engineering Technology/Technician
ABOUT SAI SRUJANA R.
I’m passionate about turning cutting-edge AI research into real-world impact. Over the last 5 years, I’ve built and deployed LLM-powered solutions and end-to-end ML pipelines that help organizations move faster, automate smarter, and make better decisions.At State Street, I developed a GPT-4 & LangChain-powered assistant that automated financial analysis and compliance reporting—cutting reporting time by 60%. I’ve also designed RAG pipelines for regulatory Q&A, anomaly detection systems in agriculture, and traffic forecasting models that improved city planning efficiency.What excites me most is building scalable, production-ready AI systems—from data engineering and cloud infrastructure to ML model deployment and observability. I thrive at the intersection of Generative AI, NLP, Cloud ML, and MLOps, where innovation meets real-world reliability.Looking to connect with AI/ML professionals, innovators, and organizations that are pushing the boundaries of what’s possible with data and intelligence.
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