Software Engineer with 1+ year of industry experience building scalable backend APIs, ML-integrated services, and cloud-native systems. Strong foundation across the full engineering stack — from system design and database optimization to model deployment and multi-tenant security. Focused on writing production-grade code that performs reliably at scale.

Currently open to Backend, ML Engineering, and Platform Engineering roles.

Sep 2024 – Jan 2026 · Nellore, India

Key Contributions:

• Architected and deployed scalable backend APIs and ML inference services across multi-tenant production environments
• Built an NLP-to-SQL pipeline enabling non-technical users to query databases through natural language
• Reduced API latency by 72% through caching layers, query indexing, and async processing refactors
• Implemented JWT-based authentication with Role-Based Access Control (RBAC) for secure tenant isolation
• Mentored junior engineers on production deployment practices and CI/CD workflows

Python · LangChain · Neo4j · FastAPI · Azure

A graph-augmented retrieval system that maps relationships between entities in large document corpora, enabling contextually rich, multi-hop question answering beyond the limitations of traditional vector search.

• Built a knowledge graph pipeline to extract and link entities, relationships, and concepts from unstructured documents
• Integrated GraphRAG with a vector store for hybrid retrieval — combining semantic similarity with structured graph traversal
• Exposed a production-ready FastAPI inference endpoint with streaming response support
• Reduced hallucination rate compared to standard RAG by grounding answers in graph-verified entity chains
• Designed for extensibility: swap-in support for different LLM backends and document ingestion formats

Flask · PostgreSQL · Azure Blob Storage · Docker

A production-grade async document storage platform built for high-concurrency enterprise workloads, featuring secure multi-tenant access and worker-pooled uploads.

• Engineered an async upload pipeline supporting 500+ concurrent users without throughput degradation
• Designed queueing + worker pooling architecture to decouple upload ingestion from processing
• Implemented JWT authentication with RBAC tenant isolation — each tenant's documents are access-controlled at the API layer
• Achieved 40% improvement in upload speed under peak load through connection pooling and blob chunking
• Containerized with Docker; deployed to Azure with environment-based configuration management

Python · TensorFlow · Flask · Azure · CNN

An end-to-end medical imaging pipeline from dataset preprocessing to a live inference API, built to assist early dermatological diagnosis.

• Trained a Convolutional Neural Network on 13,000 ISIC dermoscopy images with custom augmentation pipeline
• Achieved 87% classification accuracy across 7 lesion categories including melanoma
• Reduced false negatives by 12% through threshold calibration and class-weighted loss tuning
• Deployed as a production inference REST API on Azure with 99.5% uptime SLA
• Implemented confidence scoring on predictions for downstream clinical review workflows

Python · Flask · PostgreSQL · Transformers

A natural language interface that translates plain-English questions into executable SQL queries, reducing reliance on technical staff for routine data access.

• Designed a semantic parsing pipeline using transformer-based models fine-tuned on domain-specific schema
• Reduced manual data querying workload by 80% across internal business operations
• Handled schema introspection dynamically — works across multiple database schemas without hardcoding
• Validated output SQL for injection safety before execution, with error recovery and query explanation

• Top 10 Finalist — TerraHackathon (among national-level submissions)
• 5+ Open Source Contributions across backend and ML tooling repositories
• Engineering Mentor — guided junior engineers on production deployment, CI/CD, and system design