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AI Engineer with less than a year in LLM applications & Generative AI.
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AI Engineer with hands-on experience building production-grade LLM applications, Generative AI systems, and RAG pipelines. Shipped real-world AI integrations using Python, LangChain, FastAPI, and OpenAI/Anthropic APIs with a strong focus on experimentation, model development, and data processing. Graduating in 2026 (GPA: 8.62/10) from AMU; self-motivated builder who learns fast and ships faster.
Zakir Husain College of Engineering & Technology, Aligarh Muslim University
Bachelor of Technology · Artificial Intelligence
August 1, 2022 – June 30, 2026
Acro Technologies India Private Limited
Machine Learning Intern
October 1, 2025 – March 1, 2026
Noida, Uttar Pradesh, India
NexGen Nextopia
Machine Learning Analyst Intern
August 1, 2024 – September 1, 2024
India
Live Parking Spot Detection System
June 4, 2026 – Present
• Built a computer vision AI application achieving 98% accuracy on images and 96% on live video; reduced inference latency ~35% for real-time detection.
View ProjectBlood Pressure Prediction using PPG Signals
June 4, 2026 – Present
• Developed a deep learning pipeline (ResNet1D on MIMIC-III) for non-invasive BP estimation; processed 30GB+ of physiological time-series data end-to-end. Achieved SBP MAE 3.52 mmHg / DBP MAE 1.96 mmHg.
View ProjectPersonalized Learning Buddy with Persistent Memory
June 4, 2026 – Present
• Built a Generative AI application using LangChain and LLM orchestration for personalised education—achieving 87% faithfulness and 80% semantic similarity via advanced RAG. • Implemented multi-mode AI workflows (explain, practice, assess) with prompt engineering, persistent memory, and HyDE-style retrieval (80% Recall@K, 70% MRR). • Containerised and deployed with Docker; integrated OpenAI and Anthropic APIs with retry logic and structured logging for production reliability.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Engineer role, particularly in environments focused on innovation and practical application of AI. The diverse range of personal projects and internship experiences, from personalized learning systems to medical signal processing and computer vision, showcases a broad interest and ability to apply AI across different domains. The emphasis on building production-grade solutions and optimizing performance aligns well with a results-driven culture. The candidate's academic background in Artificial Intelligence further solidifies this fit.
Soft Skills & Operational Fit
The candidate's project descriptions highlight a self-motivated builder who learns fast and ships faster, indicating a proactive and results-oriented work attitude. The focus on production reliability, pipeline optimization, and achieving specific performance metrics (e.g., 87% faithfulness, 80% semantic similarity, 60% reduction in processing time) suggests a strong operational fit and attention to detail. The experience with diverse projects (Generative AI, deep learning for physiological data, computer vision) also points to adaptability and a broad problem-solving mindset.