I’m a full-stack AI developer building LLM-powered applications and multi-agent workflows, with a focus on production-ready systems that connect strong backend logic to a polished frontend experience. I enjoy working across the entire stack—designing APIs and authentication flows, building RAG pipelines with vector search, and orchestrating agentic logic using frameworks like LangChain and LangGraph. In my projects, I’ve implemented grounded research and hallucination-aware agent behaviors, along with semantic caching to reduce LLM token usage and improve responsiveness. I also bring an observability mindset by using tools such as LangSmith to trace agent execution and performance, so the solutions I build are both intelligent and transparent.

Snehanshu Sekhar Jena

I’m a full-stack AI developer building LLM-powered applications and multi-agent workflows, with a focus on production-ready systems that connect strong backend logic to a polished frontend experience. I enjoy working across the entire stack—designing APIs and authentication flows, building RAG pipelines with vector search, and orchestrating agentic logic using frameworks like LangChain and LangGraph. In my projects, I’ve implemented grounded research and hallucination-aware agent behaviors, along with semantic caching to reduce LLM token usage and improve responsiveness. I also bring an observability mindset by using tools such as LangSmith to trace agent execution and performance, so the solutions I build are both intelligent and transparent.

Available to hire

I’m a full-stack AI developer building LLM-powered applications and multi-agent workflows, with a focus on production-ready systems that connect strong backend logic to a polished frontend experience. I enjoy working across the entire stack—designing APIs and authentication flows, building RAG pipelines with vector search, and orchestrating agentic logic using frameworks like LangChain and LangGraph.

In my projects, I’ve implemented grounded research and hallucination-aware agent behaviors, along with semantic caching to reduce LLM token usage and improve responsiveness. I also bring an observability mindset by using tools such as LangSmith to trace agent execution and performance, so the solutions I build are both intelligent and transparent.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Intermediate
Hindi
Intermediate

Work Experience

Full Stack AI Developer (Project) at CortexWiKi
April 1, 2026 - Present
Developed a multi-agent AI research system using LangGraph to reduce hallucinations and improve source attribution. Built a 5-agent pipeline (Planner, Retrieval, Search, Guard, Answer) that ingests web and YouTube sources into a compounding knowledge base. Implemented a hybrid memory approach: Neo4j for relationship mapping and MongoDB for persistence. Added a hallucination-guard mechanism that computes real-time confidence scores and provides clickable, per-sentence source attribution. Integrated LangSmith to trace agent execution paths and monitor latency and routing decisions for full visibility.
Full Stack AI Developer (Project) at ArthFlow
June 1, 2025 - Present
Built an AI-powered finance system for streamlined expense tracking and intelligent decision support. Implemented secure authentication using JWT with refresh tokens, bcrypt hashing, and Google OAuth2. Engineered a WebSocket-based semantic cache using vector similarity search to reduce LLM token usage significantly for both guests and authenticated users. Developed a RAG pipeline using Google Gemini embeddings and MongoDB Atlas Vector Search to enable context-aware querying over uploaded financial documents with automatic PII masking and low-latency responses. Integrated Google Calendar API to schedule reminders and align financial goals with user activity.

Education

Master of Computer Application (MCA), Computer Science at Institute of Management and Information Technology
August 1, 2019 - September 1, 2022
Bachelor of Science (B.Sc) at Radhanath Rath Vigyan Degree Mahavidyalaya
July 1, 2016 - August 1, 2019

Qualifications

Full Stack Generative and Agentic AI with Python (Udemy)
December 1, 2025 - March 1, 2026
Full Stack Development Training (JAFS) (AchieversIT)
February 1, 2025 - August 1, 2025
Full Stack Web Development Program (MERN) (AlmaBetter)
November 1, 2022 - July 1, 2023

Industry Experience

Software & Internet, Education, Computers & Electronics, Financial Services

Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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