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AI Research Engineer with less than a year in AI/ML & Data Science
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Design-driven computer science undergraduate passionate about creating seamless, user-focused solutions and building intelligent AI agents. I have hands on experience in building multi agent AI Systems, RAG pipelines, and LLM powered applications using Lang Chain, OpenAI API, and Vector Databases. Also, I have a growing interest in Prompt Engineering and conversational voice AI systems.
IILM University
Bachelor of Technology · Computer Science
August 1, 2023 – Present
Welmount Appliances
AI/Data Analyst Intern
November 1, 2025 – January 31, 2026
Greater Noida, Uttar Pradesh, India
Multi-Agent Research System
February 1, 2026 – March 31, 2026
I built a system with 4 AI agents (search, scrape, write, and critique) using LangChain, GPT 4.0 mini, and Tavily Search API where each agent had its own specific role and instructions to follow. Engineered reusable prompt frameworks for a multi agent system, including a writer agent for structured report generation and a critic agent with a standardized evaluation rubric covering quality scoring, critique analysis, improvement recommendations and final verdict. Designed and wired up two custom LangChain tools Tavily Search for web search and BeautifulSoup for page scraping, writing tool descriptions precise enough that the LLM consistently chose and called the right tool at the right time.
AI Video Assistant
February 1, 2026 – Present
Built an end to end AI pipeline that ingests YouTube URLs or local audio or video files, transcribes them using OpenAI Whisper and Sarvam AI STT, and leverages LangChain LCEL chains with Mistral AI to generate meeting titles, summaries, action items, key decisions, and open questions. Implemented a production RAG system using ChromaDB and HuggingFace embeddings, chunking transcripts into 500 token segments and enabling retrieval augmented natural language QA over meeting content. Designed and implemented five reusable prompt frameworks for summarization, title generation, action item extraction, decision extraction, and question extraction, ensuring consistent structured outputs across use cases.
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with the target role of AI Research Engineer, focusing on cutting-edge AI applications like multi-agent systems and RAG. The academic projects are diverse in their application areas (research systems, video assistants) and showcase a breadth of relevant technical skills. The internship also shows practical data analysis and AI tool development. The candidate's passion for AI and continuous learning, as indicated by the summary and project work, suggests a good cultural fit for a research-oriented role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to design and implement complex systems, suggesting problem-solving and execution skills. The internship experience shows practical application of data analysis and automation. The extracurricular activity as a DC Crew Member, while not directly technical, suggests teamwork and operational involvement. However, without specific psychometric or English test results, a comprehensive assessment of soft skills like logical reasoning, work attitude, stress handling, and team collaboration is not possible.