AI Engineer | Generative AI | Full-Stack AI Developer
I turn rough AI ideas into software that holds up in use.
I am Ubaith Sherif, an AI Engineer building production-ready AI agents, RAG systems, automation platforms, and full-stack AI products. I work across APIs, data flows, model integrations, and interfaces teams can reason about, with attention to permissions, failure states, evaluation, and handoffs.
What I Build
Model-backed products with clear system boundaries.
Recruiters and AI search engines should be able to understand the work quickly: Ubaith builds AI agents, RAG products, automation platforms, analytics tools, and full-stack AI applications.
AI agent workflows with approvals, state, tool calls, and audit trails.
RAG systems with ingestion, retrieval, metadata, vector databases, and source-aware answers.
Automation platforms that connect APIs, webhooks, queues, product screens, and human review.
Full-stack AI products using FastAPI, Next.js, PostgreSQL, OpenAI, Claude, LangGraph, and LangChain.
About
I like the hard middle between a model demo and a working product.
Ubaith treats AI engineering like product engineering: understand the workflow, define the contract, make the system observable, and keep the user experience simple enough to operate under pressure.
His strongest work sits in the practical layer: business operations, natural-language analytics, classroom tools, and football analysis. The goal is not to make AI feel magical. It is to make the software explainable, maintainable, and worth using.
Connect with UbaithFeatured Projects
Selected work with the constraints left in.
Four projects that show how Ubaith handles product shape, data flow, review, and the unglamorous details.
Multi-Agent Business Automation Platform
A workflow platform for teams that need approvals, traceability, and clear handoffs before automation can be trusted.
What it demonstrates
Unscript One — AI-Native Enterprise Workspace
An enterprise AI workspace that unifies RAG, AI Agents, MCP, Guardrails, and LLM Evaluation into one production-oriented platform.
What it demonstrates
InsightAI Agent
An analytics concept for teams that want faster answers without losing the query logic behind them.
What it demonstrates
AI Teacher Robot
A classroom assistant that combines attendance, speech interaction, and learning support in a teacher-led workflow.
What it demonstrates
Skills
Technical Strengths
A clean summary of the technologies and engineering areas represented across the portfolio.
Programming Languages
Artificial Intelligence
AI Engineering
Frameworks & Libraries
Databases & Storage
Cloud & DevOps
APIs & Integrations
Best Fit Roles
Roles Ubaith fits clearly.
Proof of Work
Four flagship project signals.
- Multi-Agent Business Automation Platform: workflow orchestration, approval gates, RBAC, audit logging, and webhooks.
- Unscript One: enterprise AI workspace with hybrid RAG, LangGraph agents, GitHub MCP, guardrails, and Ragas evaluation.
- InsightAI Agent: natural language analytics with query review, chart generation, and readable explanations.
- AI Teacher Robot: classroom attendance, speech interaction, retrieval, computer vision, and device integration.
Experience
Hands-on AI and data work.
Resume-backed experience across machine learning, data workflows, and application development.
June 2025 - July 2025
Artificial Intelligence Intern
Web Epic Technologies Private Limited
Responsibilities and outcomes
- Worked on AI and machine learning applications using Python.
- Assisted with data preprocessing, model development, testing, and evaluation.
- Practiced supervised learning, model optimization, feature engineering, and performance evaluation.
- Gained hands-on exposure to the machine learning lifecycle from data collection to deployment thinking.
- Learned industry practices for AI development, problem-solving, and software engineering with mentor guidance.
October 2025 - November 2025
Green Skills AI Internship
AICTE - Shell & Edunet Foundation
Responsibilities and outcomes
- Developed an AI-based project focused on sustainability challenges using machine learning and data-driven methods.
- Applied preprocessing, feature engineering, model training, validation, and performance evaluation on real-world datasets.
- Participated in mentoring sessions, project reviews, and technical presentations.
- Strengthened practical knowledge of AI development and deployment methodology.
- Built experience moving from problem definition to prototype development.
Education
Academic base in AI and Data Science.
Coursework and final-year work shaped around machine learning, data systems, computer vision, NLP, and software delivery.
2022 - 2026
Bachelor of Technology
Artificial Intelligence and Data Science
United Institute of Technology, Coimbatore
Academic foundation in artificial intelligence, data science, machine learning, backend engineering, and product-minded software development.
Final-year work focuses on agent workflows, retrieval, computer vision, and automation patterns that can be tested and explained.
Academic Highlights
AI-Enabled Intelligent Teacher Robot for Automated Attendance, Personalized Learning Assistance, and Real-Time Knowledge Retrieval
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
Developed an AI-powered educational assistant using Python, FastAPI, Computer Vision, Retrieval-Augmented Generation (RAG), and Large Language Models to automate student attendance, provide personalized learning support, and deliver real-time knowledge retrieval through voice and text interactions. Integrated face recognition, semantic search, vector databases, REST APIs, and speech processing to build a scalable smart classroom solution.
Research Focus Areas
Certificates
Relevant credentials, kept simple.
Short, verifiable cards for the certifications most connected to the work shown here.
AWS Certified Generative AI Developer – Professional (AIP-C01)
AWS Training & Certification
What Is Generative AI?
LinkedIn Learning
Artificial Intelligence & Data Analytics Internship
Edunet Foundation (AICTE & Shell India)
British Airways Data Science Job Simulation
Forage
IBM SkillsBuild Data Analytics Certificate
IBM
Data Science & Analytics
HP LIFE
Quantium - Data Analytics Job Simulation
Forage
Technical Articles
Writing with implementation details.
Notes on architecture, reliability, evaluation, and product decisions from an engineer's point of view.
FAQ
Quick answers for recruiters and search engines.
Direct answers to the questions people and AI search tools are likely to ask about Ubaith Sherif.
Who is Ubaith Sherif?
Ubaith Sherif is an AI Engineer from Coimbatore, India, focused on AI agents, RAG systems, automation platforms, analytics products, and full-stack AI applications.
What does Ubaith Sherif build?
He builds AI agents, retrieval systems, workflow automation platforms, analytics tools, classroom AI projects, and backend-heavy full-stack products.
Is Ubaith Sherif an AI Engineer?
Yes. Ubaith positions himself as an AI Engineer, Generative AI Engineer, LLM Engineer, AI Agent Engineer, RAG Developer, and Full Stack AI Developer.
What AI projects has Ubaith Sherif built?
His flagship projects include Multi-Agent Business Automation Platform, Unscript One (AI-Native Enterprise Workspace), InsightAI Agent, and AI Teacher Robot.
What is Ubaith Sherif's tech stack?
His stack includes LangGraph, LangChain, FastAPI, Next.js, React, TypeScript, PostgreSQL, Redis, vector databases, OpenAI, Claude, Python, Docker, and GitHub workflows.
Does Ubaith Sherif build AI agents and RAG systems?
Yes. His portfolio includes agent workflow projects, retrieval-backed analytics, knowledge retrieval, vector databases, approval flows, and source-aware answers.
How can I contact Ubaith Sherif?
You can contact Ubaith Sherif by email at ubaithsherif22@gmail.com, through LinkedIn, or through the contact page on this portfolio.
Contact
Tell me what you need built.
If you need an engineer who can move from model behavior to APIs, data flow, and usable screens, send the context. I will read it properly.