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AI Engineer with less than a year in data analytics and LLM-based applications
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Assessing your cultural and operational fit
Computer Science Engineering student with experience in data analytics, AI-powered backend systems, and LLM-based applications. Skilled in Python, SQL, REST APIs, and data-driven problem solving. Experienced in building scalable AI systems, analyzing datasets, and developing analytical solutions to improve performance and efficiency. Strong interest in analytics, machine learning, GenAI applications, and business-focused AI systems.
I.K. Gujral Punjab Technical University, Jalandhar
B.Tech · Computer Science and Engineering
August 1, 2023 – Present
Magnus Global School
Higher Secondary Education · Science
June 1, 2021 – May 31, 2023
St. Joseph's English Medium School
Secondary Education
June 1, 2021 – May 31, 2021
Pinnacle Labs
Artificial Intelligence Intern
May 1, 2025 – June 1, 2025
Kolkata, West Bengal, India
Multi-LLM Orchestration & Inference Platform
February 1, 2026 – February 1, 2026
Built a multi-LLM orchestration system to dynamically route user queries across models based on query complexity and system-defined logic. Developed REST APIs using FastAPI to enable real-time inference and efficient handling of concurrent user requests. Designed and implemented model routing and fallback mechanisms to improve system reliability and response consistency. Integrated multiple LLM APIs (OpenAI/GPT-based, Claude, Gemini) for flexible and scalable response generation. Implemented latency tracking and logging systems to monitor model performance and response times. Optimized API workflows to reduce response latency and improve overall system efficiency. Structured the system using a modular architecture with separate orchestration, model client, and service layers. Demonstrated practical applications in intelligent assistants, query routing systems, and AI-powered backend services.
View ProjectComputer-Vision Object Detection System
January 1, 2026 – January 1, 2026
Built a real-time object detection system using deep learning techniques for identifying multiple objects in images and video streams. Developed a real-time inference pipeline using PyTorch and Ultralytics, enabling efficient processing of visual data. Fine-tuned pre-trained models on the COCO dataset, achieving 90% detection accuracy. Designed end-to-end computer vision workflows including image preprocessing, bounding box detection, and classification for efficient inference. Optimized model performance for low-latency predictions, reducing inference time by 20%. Improved inference speed and scalability by refining processing pipelines, achieving 25–30 FPS on video streams (local environment). Enhanced processing efficiency by 30% through optimized data pipelines and reduced computational overhead. Demonstrated practical applications in surveillance, object tracking, and smart monitoring systems.
View ProjectIntelligent Academic Chatbot Using LLM APIs
June 1, 2025 – June 1, 2025
Built an AI-powered academic chatbot using LLM APIs to assist students across multiple subjects. Designed a modular, API-driven backend architecture using REST APIs, capable of handling 50+ concurrent user requests. Integrated external LLM APIs and implemented context-aware response generation using prompt engineering techniques. Designed and experimented with model routing and fallback strategies to improve system reliability and response consistency. Applied NLP techniques to interpret user queries and enhance conversational accuracy and relevance. Optimized API usage and backend workflows, reducing response latency by 25% and lowering cost overhead. Improved response quality through prompt optimization, increasing relevance by 20–25% (qualitative improvement). Implemented structured response handling and query optimization to improve user experience. Demonstrated real-world applications in academic assistance, doubt-solving, and AI tutoring systems.
View ProjectCloud Certification
Amazon Web Services Academy
June 1, 2026 – Present
Python for Data Science
XIE
June 1, 2026 – Present
Command Line in Linux
Coursera
June 1, 2026 – Present
ReactJS & Redux
Udemy
June 1, 2026 – Present
Java Programming Certification
Unknown
June 1, 2026 – Present
SQL Certification
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show a strong interest in diverse AI applications, from LLM orchestration to computer vision and academic chatbots, indicating adaptability and a broad technical curiosity. The target role of 'AI Engineer' aligns well with the candidate's project experience and stated interests. The breadth of skills and technologies used suggests a willingness to learn and engage with various technical challenges.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking, problem-solving, and cross-functional collaboration through project descriptions. Experience with Git and Linux indicates adherence to professional software development workflows. The modular architecture approach in projects suggests good operational fit for scalable system design.