Kintur Shah — AI Researcher
I am an AI and Machine Learning Engineer focused on building intelligent, scalable, and cloud-ready systems using modern LLMs, RAG architectures, vector databases, and robust AI pipelines. My experience spans ML engineering, LLM application development, backend systems, and full-stack AI products built to solve real-world problems. AI and ML Engineering: Skilled in developing ML models, retrieval systems, embeddings, and evaluation pipelines using Python, TensorFlow, Hugging Face, scikit-learn, and LangChain. LLM and Agent Workflows: Hands-on experience designing agent-based architectures, tool-augmented reasoning, and orchestration across OpenAI, Anthropic, Vertex AI, Cohere, and open-source models. Backend Engineering: Proficient in FastAPI, Flask, Django, and Node.js to build scalable backend services deployed on AWS, Azure, GCP, Render, and Vercel. Cloud, DevOps, and MLOps: Experienced with Docker, CI/CD, serverless APIs, observability, and deploying AI workflows in production. Full-Stack AI Applications: Adept with React, JavaScript, HTML, and CSS for building responsive, data-driven interfaces with integrated AI and vector search. Data Engineering and Analytics: Strong in Python-based pipelines, feature extraction, visualization, and statistical analysis for model-ready data. Key Highlights: Built an AI Document Assistant using RAG, vector databases, and LangChain for intelligent retrieval and contextual Q&A across complex document sets. Created an AI Resume Analyzer with LLM reasoning and embeddings to offer personalized resume feedback and job-matching insights. Developed an NLP-based Movie Recommendation Engine using Transformer embeddings and semantic similarity search. Engineered a Hate Speech Detection System using BERT and LSTM models optimized for high-variance, real-world text patterns. Delivered full-stack applications like inventory systems and grocery platforms integrating SQL-backed storage and AI-enhanced search. Currently leading development of a master-sub agent orchestration framework using AWS Bedrock AgentCore Runtime, MCP, and connectors to ServiceNow, Datadog, and Splunk to automate incident triage and drive enterprise-scale observability. I hold a Master’s in Computer Science from the University of Texas at Arlington and am actively seeking opportunities in AI/ML engineering, LLM systems, RAG-based platforms, or full-stack AI roles. Let’s connect and collaborate on meaningful AI innovations.
Stackforce AI infers this person is a SaaS-focused AI and Data Engineering specialist with strong cloud capabilities.
Experience: 2 yrs
Skills
- Ai Engineering
- Cloud Computing
- Data Engineering
- Data Analysis
- Business Intelligence
- Administrative Support
- Backend Development
- Machine Learning
- Tutoring
Career Highlights
- Expert in AI and ML engineering with cloud deployment experience.
- Proven track record in building scalable AI applications.
- Strong background in data engineering and analytics.
Work Experience
Resolve Tech Solutions
AI/ML Engineer (9 mos)
Holiday Channel® | Holiday World
Data Scientist Intern (3 mos)
The University of Texas at Arlington
Data Analyst Intern (6 mos)
Student Assistant (8 mos)
CSRBOX
Data Analytics Intern (3 mos)
CreArt Solutions
Backend Development Intern (1 mo)
Capabl India
Machine Learning & AI Intern (1 mo)
Hardik Thakkar Physics Classes
Physics Tutor (6 mos)
Education
Master's degree at The University of Texas at Arlington
Bachelor of Engineering - BE at L.J. Institute Of Engg And Tech.
