Professional Overview
AI Engineer with 3.9 years of experience building enterprise-grade AI, Generative AI, and data-driven intelligent systems. Skilled in translating complex business requirements into scalable AI solutions across RAG, LLMs, Agentic AI, NLP, multimodal systems, document intelligence, and MLOps. Experienced with Python, FastAPI, LangChain, LlamaIndex,
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Developed an on-premises AI-powered invoice extraction solution
- Integrate it with SAP Workflows for PO matching
- Built and deployed Teams-based conversational AI agents on Azure platforms
- Designed retrieval-grounded, tool-integrated agent workflows
- Integrate agent workflows across multiple data sources
Key Achievements / KPIs
- Tool orchestration configuration, support diverse enterprise chatbot scenarios
- Designed and proposed AI-driven solution for diverse client requirements
- Developed an on-premises AI-powered invoice extraction solution
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Developed AI-powered document intelligence solutions
- Automated large-scale data collection and synthetic data generation workflows
- Collaborate with domain experts to validate RAG-based conversational AI system
- fine-tuned Llama3 and Phi-3 using LoRA and PEFT for improved domain adaptation
Key Achievements / KPIs
- Engineered an automated Question-Answer dataset generation pipeline
- Developed scalable ETL and data management pipelinesusing HDGAT
- Automated document classification, extraction, and summarization
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built and maintained MLOps pipelines to deploy client-side AI requirements.
- Used MLflow for experiment tracking and deployment automation.
- Performed dataanalysis,data cleaning,and visualization to support model developm
Key Achievements / KPIs
- Built and maintained MLOps pipelines to deploy client-side AI requirements.
- Integrated internal AI workflows with CI/CD pipelines
Education
Field of Study: Computer Application
Field of Study: Physics
Field of Study: Physics
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
