Lawrence Prabhakar

Full Stack Developer with 4+ years of experience building scalable enterprise applications using Java, Python, Spring Boot, React.js, and AWS. Experienced in designing microservices architectures, high-performance REST APIs, and cloud-native systems supporting large-scale financial workflows. Skilled in integrating Generative AI solutions using Python, LangChain, and LLM APIs to automate document processing and knowledge retrieval.

Proven ability to optimize system performance, improve operational efficiency, and deliver secure production software in Agile environments

Full Stack Developer at Freddie Mac (2026-02 – Present)

• Designed and developed microservices-based loan validation platform supporting high-volume mortgage processing across distributed financial systems.
• Designed scalable microservices architecture for the loan validation platform, defining service boundaries, API contracts, and database interactions to support high-volume mortgage processing workflows.
• Built and maintained RESTful APIs enabling real-time loan tracking and document management.
• Optimized PostgreSQL queries and indexing strategies, reducing API response times by 35% and improving performance for high-volume financial transactions.
• Implemented JWT-based authentication and role-based access control using Spring Security, ensuring secure access to sensitive financial data and internal APIs.
• Integrated external credit scoring and risk assessment APIs, automating loan verification workflows and reducing manual underwriting efforts.
• Developed Python-based automation services for financial document analysis and data processing, improving operational efficiency for internal teams.
• Built a Generative AI assistant using Python, LangChain, and LLM APIs to summarize loan documents and enable intelligent search across internal financial policy documentation.
• Implemented Retrieval-Augmented Generation (RAG) pipelines to allow secure querying of enterprise knowledge bases and financial documentation.
• Architected and deployed cloud-native services on AWS using EC2, S3, RDS, and API Gateway, designing scalable infrastructure to support secure financial document processing.

Software Engineer at Mphasis (2020-06 – 2024-08)

• Built backend microservices using Java and Spring Boot to support customer onboarding and insurance claims processing systems.
• Contributed to system design discussions for customer onboarding services, defining API structures, service communication patterns, and database schemas for scalable microservices deployment.
• Developed React.js-based web interfaces enabling real-time tracking of onboarding and claims status, improving operational efficiency for internal teams.
• Designed and implemented REST APIs for customer registration, claims processing, and document management across distributed enterprise applications.
• Improved database performance by optimizing MySQL and PostgreSQL queries, reducing transaction processing time for large customer datasets.
• Integrated third-party KYC verification APIs to automate identity validation processes during customer onboarding workflows.
• Deployed containerized applications on Microsoft Azure using AKS and Blob Storage, enabling reliable microservices orchestration and scalable document storage.
• Implemented automated testing using JUnit, Mockito, and Postman, improving release stability and reducing production defects.
• Developed Python scripts for data processing and API automation, improving internal reporting and reducing manual data preparation.

Master of Science in Computer Information Systems – Colorado State University (2025-12)