Experienced AI developer with a strong foundation in machine learning, deep learning, and end-to-end AI solution delivery across the banking, telecom, and apparel sectors. Proven expertise in building and deploying cutting-edge deep learning models and real-time behavior analysis systems, coupled with hands-on implementation of GenAI solutions using state-of-the-art technologies. Skilled in leveraging LLM frameworks such as LangChain, LlamaIndex, and Haystack to develop scalable, agentic applications, and in applying OpenAI APIs (GPT-4, DALL
E) for advanced NLP, vision, and multimodal use cases. Experienced in prompt engineering, instruction tuning, and LLM fine-tuning, driving tailored solutions for enterprise needs. Adept at aligning AI strategies with business goals, crafting innovative solutions that optimize performance, enhance user experience, and reduce operational costs. Demonstrated capability in evaluating and ranking ML algorithms, leading cross-functional teams, and implementing AI governance frameworks for responsible and scalable deployment. Hands-on with MLOps practices, including model deployment and monitoring using Docker, Kubernetes, MLflow, and FastAPI, and integration of data platforms like Snowflake and Power BI for real-time, AI-driven decision-making. Passionate about harnessing both classical and generative AI to build intelligent, human-centric products with global reach, and measurable business impact.
Overview
6
6
years of professional experience
Work History
Gen AI Developer
Wipro
11.2025 - Current
Designed and developed an address detection and parsing system using FastAPI and advanced prompt engineering techniques, improving parsing optimization by 80%, and reducing processing time to under one second per record.
Engineered and optimized backend APIs to ensure high performance, low latency processing for structured and unstructured address data.
Processed, cleaned, and transformed large-scale datasets to ensure data integrity, consistency, and analytical readiness.
Performed exploratory data analysis on large customer datasets to uncover behavioral trends, patterns, and actionable insights.
Collaborated effectively with cross-functional teams to support day-to-day operational objectives, and maintain delivery timelines.
Demonstrated strong adaptability by rapidly learning and implementing new tools, frameworks, and data processing methodologies.
AI Developer
IBM
09.2023 - 11.2025
Conducted patents search utilizing RAG technology to enhance information retrieval efficiency.
Executed translation tasks and fine-tuned large language models for improved performance.
Developed text-to-SQL engine for streamlined data interaction and analysis.
Created RAG solutions tailored for healthcare documents to enhance accessibility.
Engineered language modeling techniques to improve text comprehension capabilities.
Designed commercial chatbot leveraging Chat GPT and large language modeling technologies.
Constructed Q&A systems based on vector databases and Chrome DB for optimized querying.
Utilized Gemini Models, AWS Bedrock, and deep learning frameworks for advanced model development.
Researched state-of-the-art architectures and algorithms used in neural networks and convolutional networks.
Developed pipelines for automating the deployment of trained models into production environment.
Developed deep learning models using TensorFlow and PyTorch frameworks.
Conducted data preprocessing and augmentation for training datasets effectively.
Compiled, cleaned and manipulated data for proper handling.
Analyzed large datasets to identify trends and patterns in customer behaviors.
Mainframe developer
Carelon Global, Legato, UST Global
04.2020 - 09.2023
Understanding
Designed documents and prepared UTP
Functionality and existing logic
Implementing modifications as per designed document
Devising test data
Coding and Enhancements: Participating in designing and improvements of Batch programs
Handled tasks involving analysis, coding and testing of various sub-modules of the system
Preparing
Unit Test Plans and executing Unit Testing
Data for Integration testing and implementing Integration testing
Refining production data into test region to do volume test to enhance performance
Conducting Self and Peer Reviews for Deliverables
Performing Model testing with client data
Answering status calls and code walkthrough sessions
Engaged with on-call support for a production cycle
Produced ad-hoc reports into excel sheets and delivered them to end users