Software Engineer | Backend Development, Cloud Infrastructure & AI Integration

I'm a software engineer with 4+ years of experience building scalable backend systems using Java Spring Boot and Python. Currently pursuing my MS in Computer Science at Syracuse University while working as a Graduate Research Assistant developing AI-powered applications.

• Building RAG-based codebase Q&A service using Python FastAPI, LangChain, and OpenAI/Gemini APIs
• Implementing dual-layer persistence with SQLite and ChromaDB vector database
• Optimizing PostgreSQL caching layer reducing API calls by 25-30%
• Reducing developer onboarding time by 30-40% through intelligent code understanding

• Engineered Azure Event Hubs pipeline processing 50K+ real-time data points daily
• Implemented OAuth 2.0 integrations with MySQL storage
• Migrated services to Azure Logic Apps reducing infrastructure costs by 45%
• Ensured 99.9% data integrity for SOC 2 compliance

• Designed microservices architecture using Java Spring Boot serving 50K concurrent users
• Developed Spring Batch jobs processing 2M+ learner records daily
• Optimized PostgreSQL and Oracle databases reducing query time by 25%
• Implemented CI/CD pipelines with Jenkins/GitLab accelerating deployments by 5x
• Reduced deployment failures to 0.1% through automated testing

Technologies: Node.js, TypeScript, Fastify, PostgreSQL, pgvector, Redis

Full-stack system for managing conversations across multiple AI platforms (ChatGPT, Claude, Gemini, etc.)

Key Features:

• JWT authentication and session management
• WebSocket real-time updates with <100ms latency
• pgvector semantic search for conversation history
• Intelligent context compression reducing token usage by 40%
• Redis caching for high-performance retrieval

Technologies: Python, Neo4j, LangChain, Docker

Graph-based Retrieval-Augmented Generation system for healthcare data queries

Key Features:

• Neo4j ETL pipeline processing 10,000+ healthcare records
• 6 node types enabling complex relationship queries
• Retry logic ensuring 99.9% data import success
• LangChain integration for natural language understanding
• Docker containerization for easy deployment

Technologies: Python, Streamlit, Google Gemini API, scikit-learn

Intelligent resume ranking system using AI embeddings and similarity matching

Key Features:

• Google Gemini embeddings for semantic understanding
• Cosine similarity scoring for job-resume matching
• Processes 20+ resumes in under 60 seconds
• 3x speedup through parallel processing (ThreadPoolExecutor)
• Interactive Streamlit web interface

• 🔒 Google Cybersecurity Professional Certificate
  View Credential

Email: [email protected]
LinkedIn: linkedin.com/in/abhinavbajpai96
Phone: (315) 741-8647
Location: Syracuse, NY

• Building RAG-based code understanding tool using FastAPI and LangChain
• Optimizing PostgreSQL database performance for vector embeddings
• Exploring AI/ML integration patterns for enterprise applications

• Advanced PostgreSQL optimization techniques
• Vector database architectures (ChromaDB, pgvector)
• LangChain and LlamaIndex for production RAG systems
• Cloud-native application patterns on AWS and Azure

Full-time Software Engineer and Data Engineer opportunities where I can leverage my experience in:

• Backend development (Java Spring Boot, Python)
• Database optimization and architecture
• Cloud infrastructure (AWS, Azure)
• AI/ML integration and RAG systems

"Build like you're being watched by future you."
Write code that you'll be proud of six months from now.