Nandan Vallamdasu

Developer {
    name: Nandan Vallamdasu;
    role: AI Engineer & Automation Developer;
    tagline: Routing boring to AI, brilliant to brains;
    interests: High-performance inference, agentic systems, & calculated madness;
};

interface TechStack {
    inference: vLLM, llama.cpp, PyTorch, GGUF/Quantization;
    agenticAI: LangGraph, LangChain, RAG Pipelines;
    cloudData: Azure Databricks, Microsoft Fabric, Kubernetes, Docker;
    automation: n8n, Power Automate, Python, Go;
    openSource: vLLM, PyTorch, Hugging Face contributor;
};

const craft = {
    coreFocus: [
        • Designing autonomous agentic workflows & self-healing systems (LangGraph),
        • Benchmarking and optimizing local LLM inference on edge hardware,
        • Engineering scalable data pipelines (Azure Databricks, Fabric),
        • Building intelligent automations that eliminate operational friction.
    ],
    currentStack: ['Python', 'LangGraph', 'vLLM', 'Azure Databricks', 'Docker']
};

const exploration = {
    nowBuilding: ['Autonomous AI SRE Agents', 'High-Performance Edge Inference Suites'],
    goal: 'Teaching AI to reason, automate, and build with purpose.'
};

const engagement = {
    availability: 'Open to AI engineering, automation, and applied research roles.',
    funFact: 'I debug my thoughts like I debug my code — with print statements and caffeine.'
};

// Contact function
const contact = (type: ContactType): string => {
    switch (type) {
        case 'github':
            return 'https://github.com/nandan2003';
        case 'twitter':
            return 'https://x.com/NandanV76';
        case 'linkedIn':
            return 'https://www.linkedin.com/in/nandan-vallamdasu';
        case 'instagram':
            return 'https://www.instagram.com/nandan_vallamdasu';
        case 'email':
            return 'nandan.vallamdasu@zohomail.in';
        default:
            return 'Send fax.';
    }
};

Resume: {
    name: Nandan Vallamdasu,
    region: Hyderabad, India,
    signature: AI Engineer & Automation Developer | High-Performance Inference, RAG & Agentic Systems
};

Education: {
    degree: Bachelor of Technology in Computer Science and Engineering,
    institution: Malla Reddy Institute of Technology and Science,
    duration: 2020 - 2024,
    majors: Data Structures, OS, DBMS, Cloud Computing, AI & ML, C/C++
};

Certifications: [
    • Google Data Analytics Professional Certificate,
    • Microsoft Certified: Azure Data Fundamentals (DP-900),
    • Microsoft Applied Skills: Build a NLP Solution with Azure AI Language,
    • CS50x: Introduction to Computer Science (Harvard University),
    • SQL (Advanced) - HackerRank
];

// # Projects
const Projects: [
    {
        name: 'Sentinel Reliability Platform',
        description: 'Engineered an autonomous AI SRE agent that detects crashes in running Docker 
        containers and hot-patches code in real-time without human intervention.',
        techStack: ['LangGraph', 'Docker', 'OpenAI', 'Python']
    },
    {
        name: 'Edge-CPU Inference Engine',
        description: 'Engineered a rigorous benchmarking suite evaluating 8 state-of-the-art LLM 
        architectures on commodity Azure CPUs. Quantified trade-offs between throughput, memory 
        pressure, and reasoning accuracy, identifying Qwen 2.5 (3B) as the Pareto-optimal solution 
        for edge inference at 95% lower cost than GPU instances.',
        techStack: ['Python', 'C++', 'llama.cpp', 'Azure VM', 'Bash', 'Matplotlib', 'Pandas']
    },
    {
        name: 'Store Provisioning Platform',
        description: 'Built a Kubernetes-native control plane that provisions fully isolated 
        production e-commerce stores in 5 minutes with a LangGraph agent managing store lifecycle.',
        techStack: ['Kubernetes', 'Helm', 'Docker', 'LangGraph', 'Go', 'React']
    },
    {
        name: 'Azure Databricks Formula 1 Analytics',
        description: 'Developed an end-to-end data engineering pipeline analyzing F1 driver and team 
        performance, processing incremental race data through Azure Data Factory and Databricks, and 
        visualizing insights via Power BI.',
        techStack: ['Azure Databricks', 'Data Factory', 'Azure Data Lake Gen2', 'Python', 'SQL', 'Power BI']
    }
];

// # Experience
    organization: Freelance Automation & Data Projects,
    location: Remote,
    title: Automation & Data Engineer,
    duration: 2023 - Present,
    achievements: [
        • Developed workflow automation systems using n8n & Power Automate to streamline repetitive 
        business processes.

        • Designed and deployed Azure-based ETL pipelines integrating Databricks, Synapse, and Power 
        BI for analytics visualization.

        • Created intelligent dashboards and news sentiment models using Bing API and Fabric Data 
        Factory.
    ],

    organization: Prudent Autolytics,
    location: Bengaluru (Remote),
    title: Intern - RPA Developer,
    duration: Jul-2025 - Aug-2025,
    achievements: [
        • Developed a PowerApps-based timesheet management system from scratch, improving internal 
        task tracking efficiency.

        • Automated Excel-based data workflows using Python scripts, reducing manual processing time.

        • Built and deployed multiple mini-process automations using Microsoft Power Automate.
    ]
};

// # Open Source
OpenSource: [
    • Contributor: vLLM, PyTorch, Hugging Face ecosystem
];

// # Leadership / Extracurricular
Leadership: [
    • Organized 5+ large-scale technical events at Microsoft IDC with 200+ participants and 20+ 
    volunteers.

    • Facilitated collaboration across students, mentors, and industry speakers on topics like AI, 
    Data Science, and Cloud Computing.
    
    • Delivered sessions on practical applications of Azure and Power Platform in solving real-world 
    business problems.
    
    • Volunteered as a guest coordinator for the Isha Insight program, engaging with business leaders 
    including the Ex-Chairman of ISRO and CBO of Mahindra Holidays.
];

// # Skills (Focused)
Skills: {
    inference_and_ai: [vLLM, llama.cpp, PyTorch, LangGraph, LangChain, RAG Pipelines, GGUF],
    cloud_and_data: [Azure Databricks, Microsoft Fabric, Delta Lake, Kubernetes, Docker],
    automation_and_devops: [n8n, Power Automate, GitHub Actions, CI/CD],
    languages: [Python, Go, SQL, C++]
};

// # Interests
Interests: High-Performance Inference, Autonomous AI Systems, Cloud Engineering, & Calculated Madness;