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AI Engineer with less than a year in Generative AI and 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
AI/ML Engineer with hands-on experience building production-grade Generative AI applications, Retrieval-Augmented Generation (RAG) pipelines, and autonomous AI agent systems. Skilled in Python, LangGraph, FastAPI, vector databases, and LLM-powered architectures with expertise in scalable backend engineering, observability, and performance optimization. Experienced in developing intelligent workflow orchestration systems, AI-driven automation, and cloud-deployed solutions for real-world applications.
National Institute of Technology, Rourkela
Bachelor of Technology · Computer Science
August 1, 2020 – June 30, 2024
REAP IIT Madras
Project Associate
January 1, 2026 – March 31, 2026
Chennai, Tamil Nadu, India
RAG Pipeline with Production Observability
January 1, 2025 – June 1, 2026
Developed a scalable Retrieval-Augmented Generation (RAG) pipeline processing 10,000+ document chunks using optimized chunking and vector search. Improved retrieval relevance through efficient embedding strategies and context-aware document indexing techniques. Designed a three-layer caching system for embeddings, retrieval results, and LLM responses, reducing end-to-end latency by 40%. Implemented production-focused observability and performance optimization for scalable AI workflows.
View ProjectTinkler - Autonomous Coding Agent
January 1, 2025 – June 1, 2026
Developed a full-stack Electron-based coding agent capable of autonomously exploring codebases, gathering contextual information, and executing long-running development tasks. Built intelligent agent workflows for code generation, terminal interaction, code modification, and end-to-end task execution Leveraged LangGraph to orchestrate multi-step reasoning, tool usage, and autonomous software engineering workflows. Designed scalable agent architecture focused on developer productivity and autonomous task completion.
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and capability in cutting-edge AI/ML technologies, aligning well with an innovative and technically driven culture. The diversity of projects (RAG pipeline, autonomous coding agent, AI-driven audio dubbing tool) indicates a broad skill set and adaptability. The academic background from a reputable institution and a merit-based scholarship suggest a driven and high-achieving individual. The experience at REAP IIT Madras, involving scaling an AI platform and ensuring data integrity, points to a candidate who values robust and reliable systems, which is a good cultural fit for roles requiring high standards.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an ability to design and implement complex systems. The 'Project Associate' role at REAP IIT Madras suggests experience in managing technical execution and bridging product strategy with engineering, implying good operational fit and cross-functional communication skills. However, without specific behavioral assessment data, a deeper analysis of soft skills like teamwork, leadership, and adaptability is limited.