Mohsin Ali
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
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 Engineer with less than a year in LangChain & RAG pipelines
AI/ML Engineer with hands-on experience in LangChain, RAG pipelines, and Agentic AI systems. Proficient in full-stack development using Python, React, and Node.js, with practical exposure to REST APIs and database integrations gained during a software engineering internship at Simplotel. Demonstrated ability to independently design and deploy AI-powered applications, including a multi-PDF Q&A assistant and a natural language database interface. Developed automation workflows using Playwright to migrate legacy booking engines to a new platform, reducing manual effort by 80%. Seeking to contribute to production AI systems in a fast-paced engineering environment.
REVA University
Master of Computer Applications
August 1, 2024 – June 30, 2026
Hemchandracharya North Gujarat University
Bachelor of Computer Applications
August 1, 2021 – June 30, 2024
Simplotel
Software Engineer Intern
February 1, 2026 – Present
Bengaluru, Karnataka, India
Intelligent PDF Query Assistant
June 25, 2026 – Present
Built an AI-powered PDF Q&A system using LangChain and vector embeddings to enable natural language querying over unstructured documents. Implemented Retrieval-Augmented Generation (RAG) to improve answer accuracy and contextual relevance. Designed a scalable document ingestion and retrieval workflow in Python using Chroma vector stores.
Chat with MySQL Database
June 25, 2026 – Present
Built a natural language interface over a MySQL database using LangChain's SQL agent, enabling users to query relational data without writing SQL. Implemented LLM-powered SQL query generation that auto-detects database schema and translates plain English questions into accurate, executable queries.
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a practical application of AI concepts, which aligns with an innovative and problem-solving culture. The internship experience, though brief, shows exposure to a professional engineering environment. The blend of academic pursuits (Master's in progress) and practical projects indicates a continuous learning mindset. The target role of AI Engineer is well-aligned with the candidate's project focus on LangChain, RAG, and LLM agents. However, the overall experience level is low, which might require more mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to independently design and implement solutions. Participation in code reviews and agile sprints during the internship suggests an understanding of collaborative development practices. The profile highlights a desire to contribute to production AI systems, indicating a goal-oriented and practical mindset. However, without specific psychometric or English test scores, a deeper assessment of soft skills like logical reasoning, work attitude, stress handling, and team collaboration is not possible.