Hi, my name is

Kishan K.

I build intelligent solutions.

I'm an AI & Software Engineer specializing in Python, machine learning, and cloud development. I build and deploy scalable AI pipelines, full-stack applications, and intelligent automation systems.

Kishan K

About Me

Hello! I'm Kishan, an AI and Software Engineer with a strong foundation from Ramaiah Institute of Technology. I focus on the entire development lifecycle—from conceptualizing an idea to deploying robust, scalable applications.

Currently, I am at Silo Fortune, where I architect GenAI microservices and Applied AI solutions for agriculture. I thrive on technical challenges and am eager to contribute my expertise in turning complex requirements into high-impact software through explainable AI research and robust engineering.

Education

Ramaiah Institute of Technology, Bengaluru

B.E. in Artificial Intelligence and Machine Learning

2021 - 2025 | CGPA: 8.6/10

Technical Skills

Programming & AI

Python (AsyncIO)SQL Gemini (Flash/Pro)OpenAI API TensorFlowPyTorch TransformersViT/CNN

Backend & Cloud

FastAPIDjango PydanticDocker AWS (S3/RDS/SageMaker) GCPCI/CD

Databases & Tools

PostgreSQLMongoDB FAISS (Vector DB)LangChain LlamaIndexRedis StreamlitAlembic

Experience

Software Engineer - AI/ML @ Silo Fortune

Oct 2025 - Present | Bengaluru

  • Architected Kisaan Sampurna — a multimodal GenAI pipeline (Gemini 2.5 Flash + Computer Vision) delivering crop disease advisories in 12 Indian languages with 92%+ precision, handling 10,000+ daily API requests.
  • Built Real-Time Mandi Price API serving price data for 7,000+ agricultural markets with nearest-mandi auto-resolution using Haversine formula in SQL, multilingual support, and dual-source data (PostgreSQL + AWS S3).
  • Engineered AI Farm Intelligence System converting satellite indices (NDVI, NRI, EVI) into 432 farm condition fingerprints, generating 15-section advisories in 13 languages via two-level LLM cache — deployed on AWS ECS Fargate with Jenkins CI/CD.
  • Built AI Crop Stage Prediction pipeline reading 5 years of satellite imagery to detect growth cycles for 21 crops across 80+ sub-stages, with parallel asyncio Gemini calls for knowledge generation.
  • Orchestrated production-grade FastAPI microservices with PostgreSQL service isolation, Redis caching, and Docker CI/CD — reducing downtime by 40%.

AI-Automation Intern @ Sumedha Design Systems

Feb 2025 - Aug 2025 | Hyderabad

  • Streamlined multimodal extraction pipelines using GCP Vision and AWS S3 to process 10,000+ pages of VLSI documentation.
  • Engineered automated RAG systems with LlamaIndex and FAISS, reducing manual content creation time by 60% and boosting engagement by 15%.

Machine Learning Intern @ Pragami Solutions

Jan 2025 - Feb 2025 | Bengaluru

  • Delivered a full-stack Productivity Management System to streamline operations for small-scale industries.
  • Conducted research on lung disease prediction and interpretable models for healthcare datasets.

Things I've Built

Real-Time Mandi Price API

FastAPI backend serving price data for 7,000+ agricultural markets across India. Nearest-mandi auto-resolution using Haversine formula in SQL, 12-language support, dual-source data (PostgreSQL + AWS S3 Parquet), and cascade dropdowns under 5ms via in-memory cache.

FastAPI, PostgreSQL, AWS S3, Docker, SQLAlchemy, JWT

AI Crop Stage Prediction

5-layer pipeline reading 5 years of satellite imagery (NDVI, EVI, NDMI) to detect crop growth cycles for 21 crops across 80+ sub-stages. Generates pest/disease advisories via parallel asyncio Gemini calls. Delivered in 10 Indian languages via cache-first translation.

FastAPI, Gemini 2.0 Flash, AgroMonitoring API, PostgreSQL, AWS S3

AI Farm Intelligence System

Satellite indices (NDVI, NRI, EVI, DSWI) → deterministic bucketing → 432 condition fingerprints → 15-section advisory in 13 languages. Two-level LLM cache drives cost to near-zero. 6 satellite overlay images stored on AWS S3. Deployed on AWS ECS Fargate + Jenkins CI/CD.

FastAPI, Gemini, AWS S3, AWS ECS Fargate, PostgreSQL, Jenkins

Sperm Mobility Analysis

Architected a containerized microservice for automated semen analysis. Engineered a high-performance ML pipeline integrating YOLOv8 for detection and DeepSORT for kinetic tracking via asynchronous Celery workers.

FastAPI, Celery, YOLOv8, DeepSORT, Redis, AWS S3

Yield & Weather Agent

Architected a FastAPI backend integrating Agromonitoring and Google Maps APIs. Implemented a rule-based normalization engine and IST date-based caching in PostgreSQL to minimize latency.

FastAPI, PostgreSQL, Redis, Docker, Agromonitoring API

Intelligent Crop Diagnostic System

Diagnostic system identifying 360+ crop varieties in 10 languages with 94% precision using Knowledge-Based Agents and Gemini pro (APIs) models.

Python, Computer Vision, DL, ML Agents, Expert Systems

Kissan Sampurna Web

React Native frontend for agricultural ecosystem, enabling seamless crop image uploads and LLM-driven advisories with < 2s response times.

React Native, Node.js, Vite, AWS S3, Tailwind CSS

RAG for VLSI Automation

Constructed an AI-powered RAG system using Transformers to automate generation of 2,000+ technical MCQs, accelerating content creation by 3x.

Python, HuggingFace, MongoDB, AWS S3, Prompt Eng.

NLP Health Tracker

Cloud-based dashboard integrating NLP for activity logging, processing 500+ complex food queries while reducing data entry time by 40%.

React.js, Node.js, NLP APIs, Google Sheets

Productivity Management

A full-stack MERN task-tracking system for manager–employee workflows, achieving real-time data synchronization with <50ms latency while supporting over 50+ concurrent active users.

Node.js, MongoDB Atlas, React, Google TTS, Render

Waste Segregation IoT

IoT-based solution utilizing Inception ResNet V2, achieving 92.5% test accuracy across 6 distinct waste categories for environmental impact.

PyTorch, ReactJS, Flask, ESP-32

Publications

IEEE Bangalore Section, 2024

Performance Evaluation of Deep Learning Models for Predicting Alzheimer's Disease

Research focused on the comparative analysis of DL architectures for early detection and prediction using neuroimaging data.

ICAI – ARSSS, 2025

Enhancing Predictive Maintenance with SHAP and LIME: A Framework for Explainable AI

Developed a framework to make complex predictive maintenance models interpretable using XAI techniques for industrial applications.

Certifications

100 Days of Code: Python Pro ML, Data Science & GenAI Full Data Science & NLP Bootcamp MS Azure Cloud Services AWS Cloud Support Associate

What's Next?

Get In Touch

I am currently focused on building production-ready AI systems and advancing explainable AI. My inbox is always open for collaborations or opportunities!