I'm Arun Jyoti Chakraborty — I build AI systems that actually run in production.
While most students are still following tutorials, I've deployed four live AI systems on AWS EC2 — a multi-agent quantitative research platform, an enterprise RAG system, an AI financial analyst agent, and a healthcare appointment chatbot with Salesforce integration. Each one is live right now.
I'm someone who takes an AI capability and ships it into something that works, handles failure gracefully, and can be debugged at 3am when it breaks. I care about concurrency limits, fallback recovery, schema validation, and vector indexing speed.
My work sits at the intersection of agentic AI, RAG pipelines, and production deployment. I use LangChain, Google ADK, FastMCP, Gemini, FAISS, Docker, and AWS daily — not in ephemeral Jupyter notebooks, but in containerized services handling real requests.
Getting an LLM to generate a nice demo is easy. The hard part is building deterministic guardrails, preventing prompt injection, managing database transactions, and keeping p95 latency under SLA. That is the engineering half I focus on.
Seeking remote AI engineering roles where I can take full ownership of deployment, tool-calling orchestration, and end-to-end reliability. Ready to contribute code on day one.
Beyond The Terminal // Energy, Strategy & Mindset
HIGH-AGENCY BUILDERConsistent gym training and heavy workouts build the stamina required to power through intense debugging marathons.
Anticipating opponent moves several plies ahead trains the exact mindset needed to design resilient multi-agent fallback loops.
Immersive worlds, competitive gaming mechanics, and anime fuel creative perspective and high-focus mental resets.
I learn 10x faster by deploying real systems and handling production traffic than by passively memorizing exam notes.
IIT Guwahati Academic Foundation // Theory Applied in Code
[ 14 COURSES ]Mathematical foundation for ARIMA forecasting in the Algorithmic Trading Agent.
Supervised & unsupervised learning models, evaluation metrics (MAPE, F1-score).
Collaborative filtering, matrix factorization, and similarity metrics used in vector search.
Neural network architectures, attention mechanisms, and transformer foundation models.
Equity valuation, cash flow modeling, and financial ratios for the AI Financial Analyst.
Trees, graphs, and hash structures fundamental to vector indexing and DAG workflow execution.
Computational complexity, search algorithms, and concurrency isolation.
SQL modeling, ACID transactions, and persistent session storage (SqliteSessionService).
Core language mastery powering all 5 production backend microservices.
Virtualization, Docker container orchestration, AWS EC2, and Cloudflare reverse proxying.
Vector spaces, dot products, and cosine similarity underlying dense embedding retrieval in RAG.
Gradient descent, loss minimization, and constraint modeling in agentic decision chains.
Hypothesis testing, confidence intervals, and benchmark error bounds.
Regression modeling, causality testing, and macro economic trend analysis.
VERIFIED CREDENTIAL ARCHIVE
14 VERIFIEDAudited course completions, academic coursework, and corporate simulations chronologically sorted by award date.
AWS AI Practitioner Challenge
DA 210 | Time Series Analysis & Forecasting
Certificate of Internship Completion: Power BI for Business
Microsoft Azure — 25 Hour Course
Cloud Administration & Engineering — 40 Hour Course
Power BI for Business Applications — 20 Hour Course
Supervised Learning with scikit-learn
Python Certificate of Completion
Data Manipulation with pandas
Introduction to NumPy
Data Analytics Job Simulation
Python Intermediate
Python Developer
IIT Guwahati BSc (Hons.) DS & AI Orientation Course
Auditor Rating & Constructive Peer Review
Private feedback to help Arun continuously harden systems and grow as an applied engineer.