Vamsi Krishna Data Engineer
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Hi there! I am a professional Backend Developer specializing in cutting-edge technologies like Generative AI and Data Engineering. I can help you understand and build real-world projects in:

Backend Development: Creating robust APIs, servers, and databases (using Python, Node.js, SQL/NoSQL).

GenAI & Chatbots: Building intelligent chatbots and AI agents using OpenAI, LangChain, and LlamaIndex.

RAG Systems: Teaching you how to ground AI models in your own data for powerful, accurate applications.

Data Analysis & Dashboards: From data processing with Python (Pandas) to building insightful dashboards.

AI Automation: Automating tasks and workflows using AI.

Whether you are a beginner looking to understand the basics or an advanced student working on a complex project, I provide clear, step-by-step guidance. Let's build something amazing together

Subjects

  • Python Beginner-Expert

  • FastAPI (Python) Beginner-Expert

  • AI & ML Beginner-Expert

  • Large Language Models LLMs Beginner-Expert

  • RAG (Retrieval-Augmented Generation) Beginner-Expert

Experience

  • Software Engineer (Oct, 2023–Present) at Covalense Global
    A versatile and innovative Backend Developer responsible for designing, developing, and maintaining robust server-side logic, with a strong focus on integrating Generative AI, building intelligent chatbots, creating data analysis pipelines, developing interactive dashboards, implementing RAG systems, and driving automation through AI.

    Key Roles & Responsibilities
    1. Backend Application Development & Architecture
    Design, develop, and maintain scalable, secure, and high-performance backend services and APIs using appropriate technologies (e.g., Python, Node.js, Java, Go).

    Architect and implement database schemas, manage data storage, and optimize queries for relational (e.g., PostgreSQL, MySQL) and non-relational (e.g., MongoDB, Redis) databases.

    Containerize applications using Docker and orchestrate them with Kubernetes for scalable deployments.

    Implement CI/CD pipelines to automate testing and deployment processes.

    Ensure application security, data protection, and adherence to best practices.

    2. Generative AI & Intelligent Chatbot Development
    Design, build, and integrate conversational AI agents and chatbots using GenAI frameworks (e.g., OpenAI GPT, Anthropic Claude, LlamaIndex, LangChain).

    Fine-tune large language models (LLMs) for specific tasks and domains to improve accuracy and relevance.

    Implement context management, memory, and stateful conversations to enhance user experience.

    Integrate chatbots with various messaging platforms (Slack, Teams, WhatsApp) and internal systems via APIs.

    3. Data Analysis & Pipeline Engineering
    Develop and maintain ETL/ELT pipelines to collect, clean, and process structured and unstructured data from diverse sources.

    Perform statistical analysis and data mining to extract insights, identify trends, and support business decision-making.

    Utilize data analysis libraries (e.g., Pandas, NumPy in Python) and big data tools (e.g., Spark) for handling large datasets.

    Work closely with data scientists and analysts to productionize machine learning models.

    4. Dashboard & Visualization Development
    Build backend services and APIs specifically to power real-time data visualizations and business intelligence dashboards.

    Collaborate with front-end developers to ensure efficient data fetching and rendering in tools like Tableau, Power BI, Metabase, or custom React/Vue.js applications.

    Optimize data delivery for dashboards to ensure low latency and a smooth user experience.

    5. Retrieval-Augmented Generation (RAG) Applications
    Architect and implement end-to-end RAG systems to ground LLMs in proprietary and domain-specific data.

    Develop data ingestion pipelines for document parsing, chunking, and vectorization.

    Manage and optimize vector databases (e.g., Pinecone, Weaviate, PGVector, Chroma) for efficient semantic search and retrieval.

    Continuously evaluate and improve the performance of the retrieval and generation components.

    6. AI-Powered Automation
    Identify opportunities for process automation within business workflows.

    Develop and deploy automation scripts and services using AI for tasks such as document processing, data entry, content summarization, and customer support triage.

    Leverate tools like LangChain Agents and LlamaIndex for creating autonomous workflows that can interact with software and APIs.

    7. Cross-Functional Collaboration & Strategy
    Collaborate with product managers, front-end developers, and stakeholders to define technical requirements and deliver end-to-end features.

    Stay abreast of the latest advancements in AI, ML, and backend technologies, and proactively propose innovative solutions.

    Mentor junior developers and share knowledge about GenAI best practices and backend architecture.

    Participate in code reviews, system design discussions, and architectural planning.

Education

  • B.Tech (Aug, 2019–May, 2023) from Indian Institute of Information Technology Raichur–scored 8.2 CGPA

Fee details

    ₹150–500/hour (US$1.58–5.26/hour)

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