06/22/2026 updated
Premium member
100 % availableReact Native, SaaS & AI Development Specialist | Mobile Apps, MVPs & Automation
Pune, India
Worldwide
Bachelor of Engineering, Computer ScienceAbout me
I help startups and businesses build mobile apps, SaaS platforms, AI-powered products, and automation systems. My expertise includes React Native, Expo, Firebase, Node.js, OpenAI integrations, and rapid MVP development from idea to production.
AI AgentsLLMOpenAIJavaScriptApplication Programming Interfaces (APIs)Mobile Application DevelopmentSoftware as a ServiceMobile Application SoftwareNode.jsSoftware ArchitecturePrototypingSoftware PrototypingNext.jsTypeScriptReact.js
AI & Generative AI Engineering
Expertise in GenAI APIs including Gemini, OpenAI, and Anthropic, combined with advanced Prompt Engineering techniques such as Few-shot, CoT, ToT, and Chaining. Proficiency in AI Prototyping, Agentic AI, RAG, LangChain, and Hugging Face for building scalable, intelligent applications.
Full-Stack Development
Strong command of JavaScript frameworks including React, Vue.js, Next.js, Node.js, and Express, alongside Python and its data science ecosystem including Pandas, NumPy, Scikit-Learn, PyTorch, and TensorFlow. Experience building end-to-end web, mobile, and Chrome extension platforms.
Machine Learning & Modeling
Solid foundation in Classification, Regression, Neural Networks, Feature Engineering, and Model Evaluation. Hands-on experience with Human-in-the-loop ML workflows and deploying models in production SaaS environments.
SaaS Architecture & Product Systems
Deep understanding of SaaS Architecture design, Agile methodologies including Scrum and Kanban, A/B Testing, Competitive Analysis, and User Research to deliver business-driven AI products.
Vector Databases & Retrieval Systems
Practical experience with Vector DB solutions such as ChromaDB for reliable context retrieval, enabling scalable and real-time analytics for concurrent AI-driven business applications.
Cloud & Infrastructure
Familiarity with AWS Cloud, serverless infrastructure, and MCP Server setups to support horizontal scalability and deployment of multi-agent AI systems.
Automation & Workflow Engineering
Experience engineering automation workflows using Python and Google Apps Script, streamlining multi-team data operations and reducing manual efforts significantly across business processes.
NLP & Computer Vision
Applied knowledge of NLP techniques and OpenCV for building intelligent processing pipelines, including image generation, rendering, and language-based AI features.
Database Technologies
Proficiency in MongoDB and Git for version control and data management, with experience in schema design and query optimization to improve application performance and scalability.
Expertise in GenAI APIs including Gemini, OpenAI, and Anthropic, combined with advanced Prompt Engineering techniques such as Few-shot, CoT, ToT, and Chaining. Proficiency in AI Prototyping, Agentic AI, RAG, LangChain, and Hugging Face for building scalable, intelligent applications.
Full-Stack Development
Strong command of JavaScript frameworks including React, Vue.js, Next.js, Node.js, and Express, alongside Python and its data science ecosystem including Pandas, NumPy, Scikit-Learn, PyTorch, and TensorFlow. Experience building end-to-end web, mobile, and Chrome extension platforms.
Machine Learning & Modeling
Solid foundation in Classification, Regression, Neural Networks, Feature Engineering, and Model Evaluation. Hands-on experience with Human-in-the-loop ML workflows and deploying models in production SaaS environments.
SaaS Architecture & Product Systems
Deep understanding of SaaS Architecture design, Agile methodologies including Scrum and Kanban, A/B Testing, Competitive Analysis, and User Research to deliver business-driven AI products.
Vector Databases & Retrieval Systems
Practical experience with Vector DB solutions such as ChromaDB for reliable context retrieval, enabling scalable and real-time analytics for concurrent AI-driven business applications.
Cloud & Infrastructure
Familiarity with AWS Cloud, serverless infrastructure, and MCP Server setups to support horizontal scalability and deployment of multi-agent AI systems.
Automation & Workflow Engineering
Experience engineering automation workflows using Python and Google Apps Script, streamlining multi-team data operations and reducing manual efforts significantly across business processes.
NLP & Computer Vision
Applied knowledge of NLP techniques and OpenCV for building intelligent processing pipelines, including image generation, rendering, and language-based AI features.
Database Technologies
Proficiency in MongoDB and Git for version control and data management, with experience in schema design and query optimization to improve application performance and scalability.
Languages
GermanGoodEnglishFluent
Project history
Spearheaded rapid prototyping and validation of multiple AI-driven SaaS products using GenAI tools. Built and scaled end-to-end GenAI prototypes across mobile, web, and Chrome extension platforms with adaptive multi-agent workflows. Architected an AI-powered business assistant suite handling chat, voice, and review responses. Designed AI-driven operations and automation platforms integrating inventory forecasting, appointment scheduling, and CRM pipelines. Leveraged a GenAI stack with OpenAI, Gemini, and Anthropic APIs with serverless infrastructure for 10+ concurrent AI-driven applications.
Built a personalized RAG-based writing assistant using LlamaIndex, Hugging Face models, and ChromaDB to retrieve context from tagged user data and generate tailored creative guidance. Prototyped LLM features rapidly using structured prompt engineering and evaluation to improve consistent and style-aware outputs. Technologies: Python, LlamaIndex, HuggingFace models, Streamlit.
Iteratively architected a multi-agent coordination system for streamlining CRM updates, inventory management, and scheduling across distributed workflows, cutting manual intervention by 60%. Conducted user-centric design exploration and refined prompt engineering techniques to optimize LLM behavior, increasing output consistency by 20%. Technologies: FastAPI, MCP, LangGraph, Gemini API, Notebook LLM.