Raktim Bora
Bangalore, India
Raktim Bora
Full Stack Developer | AI Integration & Automation
Category : Artificial intelligence (AI)
I am a results-driven Full-Stack Developer specializing in scalable backend architecture, AI integration, and advanced workflow automation. I excel at engineering complex technical problems to design secure, high-performance systems from the ground up. My expertise lies in deploying robust APIs, custom AI agents, and automated data pipelines that optimize system efficiency.
Core Strengths & Skills
Backend Architecture: Python, FastAPI, PostgreSQL, SQLAlchemy.
AI Integration & Automation: LangChain, RAG (Retrieval-Augmented Generation), Pandas.
Full-Stack & Deployment: Docker, AWS, System Architecture.
Technical Accomplishments
Autonomous AI Agent: Engineered a robust intelligent system utilizing Python and LangChain to automate data extraction workflows and streamline complex processing tasks.
Secure Document Analysis API: Architected a highly secure, scalable backend using FastAPI and AWS to process and analyze sensitive documents while maintaining strict compliance standards.
Gig Platform Backend: Designed the database architecture and core backend endpoints for a scalable, multi-sided marketplace prototype using PostgreSQL and Docker.
Core Strengths & Skills
Backend Architecture: Python, FastAPI, PostgreSQL, SQLAlchemy.
AI Integration & Automation: LangChain, RAG (Retrieval-Augmented Generation), Pandas.
Full-Stack & Deployment: Docker, AWS, System Architecture.
Technical Accomplishments
Autonomous AI Agent: Engineered a robust intelligent system utilizing Python and LangChain to automate data extraction workflows and streamline complex processing tasks.
Secure Document Analysis API: Architected a highly secure, scalable backend using FastAPI and AWS to process and analyze sensitive documents while maintaining strict compliance standards.
Gig Platform Backend: Designed the database architecture and core backend endpoints for a scalable, multi-sided marketplace prototype using PostgreSQL and Docker.
Working hours
- Monday:08h00 To 18h00
- Tuesday:08h00 To 18h00
- Wednesday:08h00 To 18h00
- Thursday:08h00 To 18h00
- Friday:08h00 To 18h00
- Saturday:Not available
- Sunday:Not available
Impact & Accomplishments:
Engineered Custom RAG Pipelines: Designed and deployed a Retrieval-Augmented Generation system using Python and LangChain, improving the accuracy of AI-generated responses by 40% and eliminating hallucinations on proprietary data.
Automated Data Processing: Built robust data extraction pipelines using Pandas, reducing manual data processing time from hours to under 5 minutes for large datasets.
Developed High-Performance APIs: Wrapped complex AI models into scalable backend services using FastAPI, handling 10,000+ daily requests with an average response time of under 200ms.
Cloud Deployment & Scaling: Containerized the AI applications using Docker and deployed them on AWS (EC2/S3), ensuring 99.9% system uptime and secure data handling.
Engineered Custom RAG Pipelines: Designed and deployed a Retrieval-Augmented Generation system using Python and LangChain, improving the accuracy of AI-generated responses by 40% and eliminating hallucinations on proprietary data.
Automated Data Processing: Built robust data extraction pipelines using Pandas, reducing manual data processing time from hours to under 5 minutes for large datasets.
Developed High-Performance APIs: Wrapped complex AI models into scalable backend services using FastAPI, handling 10,000+ daily requests with an average response time of under 200ms.
Cloud Deployment & Scaling: Containerized the AI applications using Docker and deployed them on AWS (EC2/S3), ensuring 99.9% system uptime and secure data handling.
Impact & Accomplishments:
Architected Scalable Databases: Designed and optimized complex relational database schemas using PostgreSQL and SQLAlchemy, reducing query execution time by 35% through advanced indexing strategies.
Built and Optimized RESTful APIs: Developed core backend logic and asynchronous endpoints using Python and FastAPI, seamlessly connecting frontend applications with secure backend databases.
Streamlined Deployment Workflows: Implemented complete CI/CD pipelines and containerized microservices using Docker, cutting deployment time by 60% and eliminating local environment bugs.
Managed AWS Infrastructure: Orchestrated cloud hosting and storage using AWS, optimizing server instances to support thousands of concurrent user connections while minimizing cloud compute costs.
Architected Scalable Databases: Designed and optimized complex relational database schemas using PostgreSQL and SQLAlchemy, reducing query execution time by 35% through advanced indexing strategies.
Built and Optimized RESTful APIs: Developed core backend logic and asynchronous endpoints using Python and FastAPI, seamlessly connecting frontend applications with secure backend databases.
Streamlined Deployment Workflows: Implemented complete CI/CD pipelines and containerized microservices using Docker, cutting deployment time by 60% and eliminating local environment bugs.
Managed AWS Infrastructure: Orchestrated cloud hosting and storage using AWS, optimizing server instances to support thousands of concurrent user connections while minimizing cloud compute costs.
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