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AI Engineer with 1+ years in RAG & LLM Applications
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI ML Engineer with hands-on experience designing and deploying machine learning models and LLM-powered applications, including Retrieval-Augmented Generation (RAG) systems for enterprise document intelligence. Skilled in Python, data preprocessing, model training, vector databases, and LLM integration to build scalable, production-ready AI solutions. Strong focus on model accuracy, performance optimization, and real-world business impact.
CDAC(USM's Shriram Mantri Vidyanidhi Info Tech Academy)
Diploma · Big Data Analytics
August 1, 2024 – June 30, 2025
Galgotias University
Bachelors of Engineering · Computer Science and Engineering
August 1, 2019 – June 30, 2023
Nusummit Technologies
Associate System Analyst
June 1, 2025 – Present
Mumbai, Maharashtra, India
Local AI Assistant And LLM Benchmarking
January 1, 2023 – June 1, 2026
Built a fully local AI assistant using Python, FastAPI, and Ollama with 3B-7B parameter language models for privacy-focused offline inference workflows. Developed FastAPI-based backend APIs with modular architecture, structured JSON response generation, and schema validation using Pydantic models to ensure reliable and validated LLM outputs. Implemented automated retry handling and response correction mechanisms for malformed JSON generations, improving the stability and consistency of local AI inference pipelines. Conducted detailed inference benchmarking by measuring metrics such as Time to First Token (TTFT), total response latency, throughput, CPU utilization, memory usage, and tokens per second to evaluate model performance. Also performed temperature-based experiments (0.0 vs 0.7) to analyze determinism, output variance, creativity, and reliability trade-offs in local LLM inference systems.
Claude Certified Architect – Foundations
Anthropic
June 1, 2026 – Present
AWS Academy Cloud Data Pipeline Builder
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including a personal project on local AI and LLM benchmarking, indicates a proactive and curious mindset. The professional experience aligns well with the target role of an AI Engineer, focusing on enterprise-grade AI solutions. The breadth of skills across programming, AI technologies, frameworks, cloud, and MLOps suggests adaptability and a willingness to learn and apply diverse tools, contributing positively to cultural fit.
Soft Skills & Operational Fit
The resume highlights soft skills such as Communication, Problem-Solving, Critical Thinking, Collaboration, Attention to Detail, Adaptability, and Time Management. These are crucial for an AI Engineer role, especially in a dynamic environment. The project descriptions indicate an operational fit through structured development practices (modular architecture, schema validation) and performance-focused analysis (benchmarking).