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AI Engineer with less than a year in Generative AI applications & RAG pipelines
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Junior AI/ML Engineer with hands-on experience building Generative AI applications using LLMs, LangGraph, RAG pipelines, and workflow automation tools such as n8n. Experienced in developing AI agents, semantic search systems, FastAPI backends, and end-to-end automation workflows integrating external APIs and databases.
Savitribai Phule Pune University
Bachelor of Engineering
August 1, 2021 – June 30, 2025
KTD Vidyalaya, Shirpur (Jain)
Higher Secondary Certificate (HSC)
June 1, 2019 – May 31, 2020
KTD Vidyalaya, Shirpur (Jain)
Secondary School Certificate (SSC)
June 1, 2017 – May 31, 2018
CodeSpyder Technologies Private Limited
Gen AI Intern
June 1, 2025 – March 1, 2026
Pune, Maharashtra, India
Enterprise AI Assistant with Intent-Based Ticketing
January 1, 2025 – Present
• Developed an agentic AI assistant using LangGraph with dual-branch routing: a RAG branch for policy document Q&A and an issue-raising branch for automated ticket creation and email notifications. • Implemented LLM-based intent classification to dynamically route user queries between knowledge retrieval and issue escalation pipelines without rule-based logic. • Built document ingestion pipeline supporting PDF parsing, chunking, HuggingFace embedding generation, and Pinecone vector indexing for semantic search over internal documents. • Designed SQL-backed issue logging system with automated email notification triggers upon ticket creation, achieving end-to-end automation from user query to resolution. • Developed Streamlit frontend and FastAPI backend, enabling a complete full-stack AI application deployable as a standalone service.
AI Agent Workflow Automation using n8n
January 1, 2025 – Present
• Built an AI-powered workflow automation system in n8n, triggered through webhooks and integrated with a Streamlit frontend for real-time user interaction. • Developed an agentic workflow using a Llama 7B model capable of understanding user intent and dynamically selecting appropriate tools to complete tasks. • Integrated Gmail APIs for email creation and search operations, enabling automated email drafting and retrieval through natural language commands. • Connected Google Calendar APIs to create and search calendar events, allowing users to manage schedules directly through the AI agent. • Implemented SERP-based web search for real-time information retrieval and Google Sheets integration for structured data storage and workflow logging.
The candidate scored 58% on the Python Internship Test, indicating a foundational but not yet proficient understanding of the evaluated Python skills. There are clear areas for improvement in advanced topics and practical application.
Strengths
Limitations
Cultural Fit Analysis
The candidate's projects showcase a strong interest in practical AI applications and automation, which aligns well with an AI Engineer role. The diversity of tools and frameworks used (LangGraph, n8n, FastAPI, Streamlit, Pinecone, HuggingFace) indicates a willingness to explore and adapt to different technologies. The personal projects demonstrate initiative and a drive to build functional systems, suggesting a good fit for a dynamic and innovative team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to learning and applying new technologies. The focus on end-to-end solutions, from backend development to frontend integration and deployment, suggests a practical and results-oriented mindset. The use of n8n for workflow automation also points to an interest in efficient operational processes.