AI Engineer with less than a year in AI/ML and Data Engineering
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As an Associate Data Scientist with 8 months of experience, I specialize in engineering enterprise-grade Agentic AI solutions, leveraging advanced frameworks like LangGraph, LangChain, and Semantic Kernel for production deployments. My expertise includes building intelligent systems such as Human-in-the-Loop AI, GraphRAG, and secure Text-to-SQL agents, along with implementing RAG pipelines using diverse databases. I am proficient in the Databricks AI ecosystem and excel in time-series forecasting and implementing Stable Diffusion models for creative applications. My project work further demonstrates strong capabilities in multi-agent NL-to-SQL systems and universal memory layers for LLMs.
JK Lakshmipat University
B.Tech · Computer Science Engineering
August 1, 2022 – June 30, 2026
Celebal Technologies
Associate Data Scientist
February 1, 2026 – Present
India
Digital Hercules Innovations
AI & ML Intern
June 1, 2024 – September 1, 2024
India
MindLayer (Universal Memory Layer)
June 24, 2026 – Present
Engineered a universal memory layer enabling seamless conversation continuity across multiple LLM providers (OpenAI GPT-4, Google Gemini, Anthropic Claude, Groq Llama/Mixtral) with intelligent FAISS vector search and hybrid retrieval strategies. Designed a unified API architecture with persistent SQLite storage, allowing model switching while maintaining full conversation history and context.
View ProjectManan (Mental Health Companion App)
June 24, 2026 – Present
Developed a privacy-first mental health app utilizing Multimodal Emotion Analysis (Face, Voice, Text) via TensorFlow and Transformers, with an AI chatbot and real-time animated visualizations. Secured user data with Row-Level Security in Supabase, ensuring full compliance with privacy standards.
View ProjectText-to-SQL Agentic System
June 24, 2026 – Present
Built a multi-agent NL-to-SQL pipeline using Azure OpenAI GPT-40-mini and Semantic Kernel, covering query understanding, SQL generation, validation, execution, and natural language answer generation. Implemented FAISS vector search over database schema embeddings to retrieve top-3 relevant tables per query, reducing LLM token consumption by 60-70%; achieved 100% pass rate across 64 unit tests with 5-layer SQL injection defense.
View ProjectEnhancing Assistive Communication through IoT-Based Hand Gesture Recognition
CCPIS 2025
January 1, 2025 – Present
Enhancing Assistive Communication through IoT-Based Hand Gesture Recognition
RI2C 2025
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in diverse AI applications, from mental health companions to enterprise agentic systems and universal memory layers. This breadth of interest aligns well with an innovative and dynamic AI engineering environment. The involvement in publications also suggests a proactive and research-oriented mindset. The experience with various tools and platforms indicates adaptability. However, the candidate is still pursuing a B.Tech degree, which might imply less real-world team collaboration experience compared to a seasoned professional, potentially impacting cultural integration in a senior role without further validation.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to work on complex, multi-faceted AI systems. The focus on privacy-first design and robust security (e.g., SQL injection defense, Row-Level Security) suggests attention to detail and responsible AI development. The experience with migrating production platforms indicates an understanding of operational continuity and deployment considerations. However, without direct interview data, specific soft skills like teamwork, leadership, or communication in a collaborative setting cannot be fully assessed.