Professional Experience

Dailoqa

AI/ML Engineer
Apr 2025 – present | Noida, India
  • •Designed a modular multi-agent RAG architecture integrating vector + graph retrieval, enabling contextual document and reducing retrieval latency by 40%.
  • •Built an MCP (Model Context Protocol) layer for unified tool-calling and agent orchestration, cutting integration overhead by 35%.
  • •Developed a cloud-agnostic ingestion pipeline for 10K+ documents (Azure, AWS, local) using semantic chunking + dynamic index routing, boosting hybrid-query precision by 30%.
  • •Delivered a Dockerized FastAPI backend, enabling consistent deployments across cloud/local with <5-minute rollout cycles and 70% reduction in setup time.
  • •Implemented multi-layered safeguards (prompt injection defense, toxicity filters, RBAC), reducing unsafe queries by 95%.
  • •Mentored a team of 3 engineers, leading sprints, reviews, and architecture discussions.

    • Stealth Startup

    AI Engineer
    Jan 2024 – Apr 2025 | Remote
  • •Built a Helpdesk Assessment System categorizing 5M+ tickets (Jira/Salesforce) into topic clusters for automated CRM reporting.
  • •Automated knowledge article generation, reducing LLM token usage and improving query resolution efficiency by 30%.
  • •Reduced customer query times using AI-trained knowledge articles, improving response accuracy by 20% and lowering costs.
  • •Designed multi-agent workflows using LangGraph, increasing workflow efficiency by 25%.
  • •Built a high-precision RAG system, cutting retrieval time from 10–15 minutes to <1 minute (90% faster).
  • •Led Elite Robots’ EC-series arm integration: collected 100GB+ robotic sensor data, built a 50-tag InfluxDB pipeline, and automated control parameters in Python.
  • •Fine-tuned LLMs on domain-specific corpora and built robust PDF/scanned-document extraction pipelines, reducing manual review effort by 60%.

    • National Institute of Technology Trichy (NIT Trichy)

    Summer Intern
    May 2023 – Jul 2023Trichy, Remote
  • •Conducted 6+ months of network lateral movement research, identifying and mitigating threats, and publishing actionable insights.
  • •Implemented deception & anomaly-detection ML techniques, reducing false positives by 15% and improving incident response accuracy.
    • Education

    Oriental Institute of Science and Technology

    2020 – 2024 | Bhopal

    Bachelor of Technology (B.Tech) - Computer Science and Engineering - (Data Science) GPA-8.65

    Projects
  • •Created an ML evaluation/selection toolkit improving experimentation speed by 25%.
  • •Published on PyPI, achieving 1,000+ downloads with seamless pip install integration.
  • •Engineered a hybrid RAG system combining embeddings + BM25 + reranking.
  • •Improved relevance by 35%, cut retrieval latency by 50%, and boosted precision for complex queries by 40%.
  • •Deployed via FastAPI with dynamic caching and autoscaling.
  • •Built a production-grade microservice supporting 5+ VLM providers with fallback routing.
  • •Extracted documents to Markdown/JSON/HTML/TXT with OCR, table parsing, and image description.
  • •Containerized with Docker and published to Docker Hub, achieving <3s cold start and production-ready deployment
  • •Delivered complete project lifecycle: requirements gathering → architecture → development → testing → documentation → Docker/PyPI publishing → GitHub release (v1.0.0)
    • Publications (70+ Citations)
    Skills
    Programming: Python, Java, Cypher Query Language, SQL
    AI/ML: LLMs, LangGraph, RAG, Autogen, Agentic AI, HuggingFace, NLP, MCP.
    Tools: Git/GitHub/Gitlab, CI/CD, Docker, Linux, RAGAS
    Frameworks: FastAPI, Streamlit, Langchain, Docling, scikit-learn
    Cloud: Microsoft Azure, Azure AI Foundry, Amazon AWS.
    Databases: Vector DBs (ChromaDB, Pinecone, Opensearch), Neo4j, Relational
    Certificates