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AI Engineer with 1+ years in Generative AI & Agentic Systems
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Assessing your cultural and operational fit
Results-driven AI/ML Engineer with hands-on experience building LLM-powered applications, agentic AI systems, RAG pipelines, and bot automation frameworks. Proficient in Python, LangChain, LangGraph, and MCP (Model Context Protocol) with a proven record of delivering ML models achieving ~90% accuracy and deploying production-ready AI solutions. Currently contributing to agentic AI and bot-builder development at Combat Solutions. Seeking roles in AI/ML Engineering, Generative AI, or Data Science.
Alard College of Engineering and Management
Bachelor of Engineering (B.E.) · Artificial Intelligence & Machine Learning
N/A – July 1, 2025
Combat Solutions
AI/ML Engineer
April 1, 2025 – Present
Pune, Maharashtra, India
NMD Infotech
Data Scientist Intern
May 1, 2024 – November 1, 2024
Pune, Maharashtra, India
Agentic AI Bot Builder Platform
June 24, 2026 – Present
Designed and built a Bot Builder framework to configure, deploy, and manage conversational AI bots with minimal code, supporting multiple LLM backends. Integrated MCP servers to provide agents with real-time access to external tools, APIs, and data sources. Used LangGraph to define stateful agentic workflows with branching, looping, and multi-agent handoff capabilities. Implemented tool-calling agents with dynamic task routing, memory persistence, and context-aware response generation. Built a supervisor-agent architecture using LangGraph to coordinate specialised sub-agents (retrieval, summarisation, Q&A) for complex query resolution. Implemented agent memory, state management, and conditional graph edges for dynamic workflow control. Enabled cross-agent tool use including web search, document retrieval, and structured data extraction.
Document Question Answering System (RAG)
June 24, 2026 – Present
Developed an end-to-end LLM-based Q&A system for PDFs using Retrieval-Augmented Generation (RAG). Implemented document loading, semantic text chunking, vector embeddings, and FAISS-based similarity search. Integrated GPT/LLaMA to generate accurate, context-aware answers grounded in source documents.
Basics of Python
Infosys Springboard
June 1, 2026 – Present
Generative AI Landscape
Infosys Springboard
June 1, 2026 – Present
OpenAI GPT Models
Infosys Springboard
June 1, 2026 – Present
Data Science Training
NMD Pvt. Ltd.
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience with diverse AI projects (agentic systems, RAG, conversational AI, traditional ML) and exposure to different frameworks (LangGraph, LangChain, TensorFlow, Keras) suggests adaptability and a broad interest in the AI domain. The current role as an AI/ML Engineer aligns well with the target role of an AI Engineer, indicating a good cultural fit for a technically driven environment focused on cutting-edge AI development. The educational background in AI/ML further reinforces this alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate business requirements into AI solutions and collaborate with cross-functional teams. The detailed project descriptions suggest good problem-solving and implementation skills. However, without direct assessment data, specific soft skills like leadership, conflict resolution, or advanced communication in a team setting cannot be fully evaluated.