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AI Engineer with 2+ years in GenAI, RAG, and Computer Vision
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Assessing your cultural and operational fit
AI/ML Engineer with 2+ years of experience in building production-grade GenAI, RAG, Agentic AI, and Computer Vision applications. Skilled in developing multi-agent workflows using LangGraph, fine-tuning LLMs with LoRA/QLORA, and designing intelligent AI systems for real-world problem solving. Experienced in NLP, deep learning, and scalable AI application development, with a strong focus on improving accuracy, automation, and user experience through practical AI solutions.
Hirasugar Institute Of Technology
Bachelor of Engineering
August 1, 2020 – June 30, 2023
Conmove Pvt Ltd
AI/ML Engineer
May 1, 2024 – Present
Pune, Maharashtra, India
Python, SQL, Data Science, Machine Learning, Artificial Inteligence, Probability Statistics certification
Seven Mentor PVT LTD
June 1, 2026 – Present
Generative AI Certification
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from conversational AI and computer vision to multi-agent research systems, indicates adaptability and a broad interest in AI applications. Their experience with modern AI stacks (LangGraph, LangChain, LLMs) and cloud deployment (AWS, Docker) aligns well with a forward-thinking, innovative culture. The focus on practical, impactful solutions suggests a pragmatic approach that would fit well in a product-driven environment. The candidate's recent graduation and current role indicate a strong drive for continuous learning and application of new technologies.
Soft Skills & Operational Fit
The candidate's resume demonstrates strong problem-solving skills through the development of complex AI solutions for real-world business challenges. Their experience in multi-agent systems and MLOps suggests an organized and systematic approach to development and deployment. The focus on reducing manual effort and improving efficiency indicates a results-oriented mindset. While direct evidence of teamwork or stress handling is not explicitly detailed, the nature of their project work implies collaboration and the ability to manage complex technical tasks.