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AI Engineer with less than a year in AI Systems and Distributed Data Systems
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Assessing your cultural and operational fit
Computer Science student specializing in AI systems and backend engineering with experience building containerized microservices, retrieval-based AI platforms, and multi-agent systems. Skilled in Python, FastAPI, Docker, CI/CD pipelines, and distributed data systems with strong foundations in algorithms, operating systems, and database systems.
GLA University
B.Tech · Computer Science (AI/ML & IoT)
August 1, 2023 – Present
Annam.AI — Centre of Excellence, IIT Ropar
AI Project Intern | Team Lead | Internship
May 1, 2025 – July 31, 2025
Rupnagar, Punjab, India
Hotel Intelligence Agent & MCP Server
January 1, 2026 – Present
Built a state-aware AI service using LangGraph to automate MongoDB analytics through backend APIs with cyclic reasoning and query correction. Developed a custom Model Context Protocol (MCP) server exposing 20+ tools for schema discovery and aggregation pipelines for automated data analysis workflows. Implemented Redis-based persistence enabling sub-50ms state recovery across concurrent API requests.
Pragati AI: Intelligent Multi-Agent Decision Platform
October 1, 2025 – Present
Designed an adaptive RAG pipeline with routing strategies for simple and multi-hop reasoning queries. Architected a LangGraph-based agent orchestration system coordinating 15+ specialized agents for complex agricultural decision workflows. Implemented Redis-based persistence to maintain long-running workflows and session states across reasoning steps.
Cultural Fit Analysis
The candidate's projects are diverse, focusing on agricultural AI and hotel intelligence, showcasing adaptability and a broad interest in applying AI to different domains. The experience as a team lead at a Centre of Excellence indicates a collaborative spirit and a drive for impactful work. The specialization in AI/ML & IoT aligns well with an AI Engineer role, suggesting a strong intrinsic motivation for the field. However, the limited professional experience (internship only) means the breadth of exposure to different team dynamics and corporate cultures is still developing.
Soft Skills & Operational Fit
The candidate demonstrates leadership potential through their intern team lead role and project management experience. Their focus on building practical AI solutions suggests a results-oriented approach. The project descriptions indicate an ability to work with complex systems and manage state, which is crucial for operational fit in AI engineering roles. However, without specific psychometric or English test scores, a deeper assessment of soft skills like communication clarity, stress handling, and team collaboration is limited.