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AI Engineer with 1+ years in Generative AI, Python & Cloud.
AI Engineer at PwC India with hands-on experience in designing, developing, and deploying enterprise-grade AI and backend systems within large-scale, consulting-driven environments. Proficient in building scalable, high-performance microservices using Python, FastAPI, and RESTful architectures, along with developing data-intensive applications and robust data pipelines to support business-critical workflows. Demonstrates strong expertise in Generative AI technologies, including Retrieval-Augmented Generation (RAG), LangChain orchestration, prompt engineering, and end-to-end LLM-based application development for real world, business-driven use cases. Experienced in integrating AI capabilities with structured and unstructured data sources to deliver context-aware, intelligent solutions. Possesses a solid foundation in database management (MySQL, MSSQL), API integrations, and system design principles, with a focus on delivering secure, scalable, and production-ready solutions aligned with Agile methodologies and the Software Development Lifecycle (SDLC). Adept at optimizing system performance, ensuring data reliability, and maintaining high standards of code quality and maintainability. Actively expanding expertise in cloud-native AI and Hybrid Cloud ecosystems, including AWS Bedrock and enterprise AI platforms, with a focus on deploying scalable and secure AI solutions. Recognized for strong analytical thinking, problem-solving capabilities, and the ability to quickly adapt to evolving technologies while contributing effectively in fast-paced, enterprise-level engineering environments.
College of Engineering And Management Kolaghat
Bachelor Of Technology · Computer Science And Engineering
N/A – June 30, 2025
Demari High School
10+2(WBCHSE)
N/A – May 31, 2021
Demari High School
10(WBBSE)
N/A – May 31, 2019
PwC India (Deputed via Aiinhome Technologies Pvt Ltd.)
Artificial Intelligence Engineer
January 1, 2026 – Present
Kolkata, West Bengal, India
Aiinhome Technologies Pvt. Ltd.
Junior Software Developer
July 1, 2025 – December 31, 2025
India
PCS Global Pvt.Ltd.
Software Developer Trainee
December 1, 2024 – June 30, 2025
India
AI-Powered Data Analytics Portal
June 27, 2026 – Present
Developed an AI-driven analytics platform enabling users to extract insights from high-volume structured datasets using natural language queries. Implemented Retrieval-Augmented Generation (RAG) with LangChain to combine data processing pipelines with LLM-based contextual response generation, delivering accurate insights, automated summaries, and reports. Role: Backend and Python Developer ✓ Implemented end-to-end RAG pipeline using LangChain (data ingestion → chunking → retrieval → LLM response generation) ✓ Developed RESTful backend services using Flask to enable scalable, API-driven analytics workflows ✓ Built high-performance data pipelines using Pandas for processing and aggregating large datasets ✓ Integrated LLM APIs (OpenAI, Gemini, Mistral) for conversational analytics and automated reporting ✓ Optimized prompt design to enhance contextual accuracy and response relevance ✓ Improved data analysis efficiency and reduced manual effort through AI-driven automation
DAgent - Multi-Agent Data Interaction & Analytics System
June 27, 2026 – Present
Developed a multi-agent Generative AI system enabling users to connect, query, and analyze data from multiple sources (MySQL, MSSQL, Google Sheets, CSV, and web search) through natural language interaction. Implemented Retrieval-Augmented Generation (RAG) with LangChain to deliver accurate, data-grounded insights, automated reports, and visualizations. Role: GenAI Developer ✓ Designed and implemented a multi-agent architecture to handle diverse data sources (MySQL, MSSQL, Google Sheets, CSV, Web APIs) ✓ Built end-to-end RAG pipelines using LangChain for context-aware data retrieval and response generation & a conversational interfaces enabling users to interact with connected data using natural language queries ✓ Implemented backend logic for automated report generation and data visualizations (bar charts, pie charts) Integrated structured and unstructured data into a unified AI interaction layer
AI Recipe Generator
June 27, 2026 – Present
Developed AI-driven content generation systems leveraging open-source LLMs to create context-aware recipes and news-based outputs. Implemented prompt engineering techniques to generate structured, relevant, and high-quality responses, enabling automated content creation and improved user interaction. Role: GenAI Developer ✓ Designed and implemented LLM-based content generation using Mistral for recipe and news dataset applications ✓ Developed and optimized prompt engineering strategies to improve response accuracy and contextual relevance ✓ Built automated workflows for generating structured outputs from unstructured inputs ✓ Integrated LLM capabilities into application pipelines for dynamic and scalable content generation ✓ Utilized Git for version control and collaborative development ✓ Enhanced content generation efficiency by automating manual creation processes
Cultural Fit Analysis
The candidate's project experience demonstrates a strong focus on practical, business-driven AI solutions, which aligns well with a consulting environment. The diversity of projects (data analytics, multi-agent systems, content generation) shows adaptability and a broad interest in AI applications. The mention of working in a 'fast-paced, enterprise-level engineering environment' further supports cultural fit for a dynamic role. However, the candidate's experience level is relatively junior, which might require mentorship in a senior-level role.
Soft Skills & Operational Fit
The candidate's resume highlights experience in Agile methodologies, SDLC, problem-solving, and collaborative teamwork, indicating a good operational fit. The ability to work with clients for requirement gathering suggests strong communication and interpersonal skills, which are valuable in a consulting-driven environment like PwC. However, without specific assessment scores for communication or psychometric tests, a deeper evaluation of these soft skills is limited.