Sai Sujay Anamangandla
Software Engineering Student
Data engineering and AI development focused. Building scalable solutions with modern technologies.
About Me
I'm a passionate Software Engineering student at the University of Western Ontario, currently gaining with hands on experience in developing data driven solutions to reduce manual work. With a deep passion in AI, I want to explore AI and Data related solutions to solve real world problems.
Education

University of Western Ontario
Bachelor of Engineering in Software Engineering
Relevant Courses:
Experience
Data Engineering Intern
PepsiCo
- •Engineered scalable distributed data pipelines via Azure Databricks (PySpark, SQL, Pandas) to fuel predictive modeling and AI driven optimization, integrating CI/CD workflows to improve data throughput by 25%.
- •Built a real time fleet tracking system using RESTful APIs (Python, Node) integrating Power Apps to sync logistics data, reducing manual entry by 30% ensuring instant verifications through cloud infrastructure for drivers.
- •Developed robust backend services with OAuth/JWT authentication and modular ingestion pipelines, deployed using Docker containerization to power reliable microservices, optimizing availability of ML/AI research datasets.
- •Automated reporting and data ingestion on PowerBI via Python and Azure Workflows, boosting insight by 40%.
Data Engineering Intern
iA Financial
- •Developed Python ETL automation pipelines to streamline big data migration of financial datasets within scalable ML platforms, reducing processing latency by 15%, ensuring 100% data quality in Salesforce CRM.
- •Leverage Salesforce CRM, Maestro, OOKIOK, and Merx to generate secure sales and compliance reports, manage client data and records, and streamline encrypted file transfers, improving department operational efficiency by 20%.
- •Monitored and secured sensitive client data in Salesforce CRM Service Cloud, implementing controls aligned with cyber security and regulatory standards to guarantee 100% software integrity and ensure accurate reporting.
- •Collaborated with cross-functional collaborating teams to optimize automation workflows ensuring 100% data security.
Founder and Co-President
FIRST Robotics Team
- •Directed C++ embedded software cycle (design, testing, optimization), applying Git for version control, validating perception logic, and debugging real time latencies, increasing system reliability and robot performance by 25%.
- •Founded and led the team's autonomy stack to architect the system logic which implemented motion planning, behavior prediction models, and embedded control strategies, ensuring seamless execution in dynamic environments.
- •Programmed autonomous vision and control systems in C++ and Java, integrating lidar and camera based perception, positioning algorithms, and sensor fusion techniques to enhance robot navigation and reliability by 20%.
Projects
Decentralized Polling System on Solana Blockchain
Developed a tamper free polling system using Solana Blockchain smart contracts to ensure secure voting and integrity.
- ∗Developed a tamper free polling system using Solana Blockchain smart contracts to ensure secure voting and integrity.
- ∗Built Python AI Agents with Gemini API to explain complex polling and monitor large whale polling activity.
- ∗Leveraged DAO frameworks to build predictive simulations for AI agents to test consensus and risk models.
- ∗Integrated third party wallets and implemented cryptographic protocols for user authentication and to reduce risk.
Campus Safety Alert App
Developed an app with a simple alert button to contact campus police and foot patrol when in danger.
- ∗Built a React Native mobile app with a one touch alert system linking students campus police and foot patrol.
- ∗Created a component-based UI in HTML, CSS, and JavaScript optimized for accessibility and real time visibility.
- ∗Designed a SQL databases on a VM with secure authentication, integrating Google and Apple OAuth2 sign in.
- ∗Developed RESTful APIs (Node.js and Express.js) to support map rendering, user matching, and request routing.
AI Chatbot for Western University Information
Built a context-aware AI Chatbot capable of answering detailed natural language queries related to Western University.
- ∗Developed a context aware LLM pipeline using Foundational Model and Retrieval Augmented Generation (RAG) to answer natural language queries from vast unstructured datasets based on admissions, and student services.
- ∗Designed and validated the ML/DL system architecture with a focus on algorithmic efficiency for low-latency inference, leveraging FAISS vector search and PyTorch model integration in a production deployment aligned with ML practices.
- ∗Generated vector embeddings with OpenAI and indexed them in FAISS to enable fast simlarity matching.
- ∗Built a Streamlit chatbot interface with optional React integration for multi platform deployment and better UX.