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    Job · 15305547

    SURAT · INTERNSHIP

    Python & Generative AI Engineer Professional

    Cloudaura Academy logo

    Cloudaura Academy

    Surat · onsite · Posted 49d ago

    Sourced fromNaukri
    Undisclosed5–10 yrsinternshipSurat

    About a minute. You'll make an account on the way through.

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    Section · 01

    About this role



    Python & Generative AI Engineering: From Basics to AI Agents
    As Surats leading institute for AI & Python training, SkillPlus Academy offers hands-on Generative AI Engineering, RAG Pipelines, and AI Agent development - available offline in Surat and live online worldwide. Our industry-aligned curriculum covers tools like LangGraph, Docker, and OpenAI/Gemini APIs, providing the skills to build scalable AI solutions. With included internships and placement support, we ensure students and professionals from Surat to Rajkot are job-ready for the future of tech.
    Fetching Python & Gen AI Jobs Hiring Now in India
    Source:
    Duration: 12 Weeks Mode: Live Online
    Real Classroom Feel Projects & Assignments Industry + Job Ready Lifetime LMS Access
    Indian Residents
    24,999
    Overseas Std.
    $349


    Master Python & Generative AI
    SkillPlus Academy is Surats most advanced Generative AI training institute, specializing in Python programming, RAG Pipelines, and AI Agent development with hands-on labs and live industrial projects. Our mentor-driven curriculum is optimized for 2026 tech standards, covering LangGraph workflows, Docker containerization, and Model Context Protocol (MCP) to prepare you for high-impact roles like AI Engineer and LLM Developer. Unlike generic coaching centers, our AI Engineering course in Surat focus exclusively on building production-ready intelligent systems-ensuring every module, from Pydantic to Vector Databases, is dedicated to making you a professional Python & AI Solutions expert.


    Python, RAG & AI Agents Curriculum
    Phase 1 Modern Python & Engineering Foundations
    Module 1
    Advanced Python & Pydantic
    Mastering Clean Code & Logic
    Python Fundamentals
    Mastering Lists, Dicts, Generators, and Asynchronous Programming (asyncio)
    Pydantic & Data Validation
    Building robust data models and handling Type Hints for AI pipelines
    OOP for AI
    Classes, Objects, and Design Patterns for modular AI systems
    Module 2
    Engineering Essentials (Git & Docker)
    Production-Ready Environments
    Version Control
    Mastering Git workflows, Branching, and Collaborative coding on GitHub
    Dockerization
    Containerizing AI apps for consistent deployment across cloud environments
    Phase 2 LLM Implementation & RAG Systems
    Module 3
    LLM Foundations & Prompt Engineering
    Interacting with Foundation Models
    LLM Architectures
    Understanding Transformers, Attention mechanisms, and Tokenization
    Advanced Prompting
    Few-shot, Chain-of-Thought, and System Prompts for OpenAI & Gemini
    Local LLMs with Ollama
    Running and integrating open-source models (Llama 3, Mistral) locally
    Module 4
    Retrieval-Augmented Generation (RAG)
    Building Private Knowledge AI
    Vector Databases
    Understanding Pinecone, ChromaDB, and Embedding models
    Document Processing
    Chunking strategies, Metadata filtering, and knowledge retrieval logic
    Project
    Developing a "Talk to your PDF" Private AI System
    Phase 3 Agentic AI & MCP Protocol
    Module 5
    LangGraph & AI Agents
    Stateful Multi-Agent Workflows
    Autonomous Agents
    Building loops and reasoning systems that can use external tools
    LangGraph Workflows
    Developing state-managed graphs for complex, multi-step AI tasks
    Module 6
    Model Context Protocol (MCP) & Deployment
    Connecting AI to Everything
    MCP Integration
    Building MCP Servers to connect LLMs with Databases, APIs, and OS tools
    Cloud Deployment
    Deploying AI Agents on Cloud platforms for production scaling
    Final Capstone
    Build and Present a Fully Autonomous AI Solution

    AI Engineer Career Path & Salary Insights
    Master the future of Tech - move from Python Developer to AI Solutions Architect with structured industry stages.
    01
    Entry 0 2 Years


    Python Developer / Associate AI Engineer
    Starting Your AI Engineering Journey
    Expected Salary
    5 9 LPA
    Industry Data (2026)
    Build robust applications using Python & Pydantic, manage environments with Docker, and integrate basic LLM APIs (OpenAI/Gemini) for automation tasks.
    Python OOP Docker LLM APIs
    02
    Professional 2 5 Years


    Gen AI Engineer / LLM Specialist
    Mastering RAG & Agentic Workflows
    Expected Salary
    10 22 LPA
    Industry Data (2026)
    Develop advanced RAG pipelines, build stateful AI agents using LangGraph, and implement vector databases for long-term AI memory and knowledge retrieval.
    LangGraph RAG Systems AI Agents
    03
    Expert 5+ Years


    AI Solutions Architect / Head of AI
    Leading Enterprise AI Strategy
    Expected Salary
    25 55L+ LPA
    Industry Trends (2026)
    Design scalable AI architectures, lead multi-modal AI projects, and implement Model Context Protocol (MCP) for enterprise-wide tool integration and governance.
    System Design MCP Protocol AI Strategy
    Salary ranges are indicative based on industry data (2026) sourced from , & . Actual salaries may vary by location, skills & experience.


    Python & Gen AI: FAQs
    01
    Prerequisites
    No prior experience is needed. We start from Python fundamentals and gradually move to advanced Generative AI concepts like RAG Pipelines and AI Agents.
    02
    Curriculum
    The course covers Advanced Python, Pydantic, Docker, LLM Prompt Engineering, RAG Systems, Vector Databases, LangGraph, AI Agents, and Model Context Protocol (MCP) for production deployment.
    03
    Mode
    Yes. The course is available both offline at our Surat campus and live online for students from Ahmedabad, Vadodara, Rajkot, and anywhere worldwide.
    04
    Course Comparison
    This course focuses on building LLM-powered applications, AI Agents, and RAG Pipelines. Data Science focuses on predictive modeling and machine learning algorithms. They are separate specializations that complement each other.
    05
    Tools
    You will work with OpenAI and Gemini APIs, LangGraph, Docker, Pinecone, ChromaDB, Ollama for local LLMs, and Model Context Protocol (MCP) for enterprise AI integration.
    06
    Placement
    We provide a mandatory Industry Internship, portfolio development, mock interviews, and alumni network connections to help you land roles like AI Engineer or LLM Developer.


    Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

    Sourced from naukri

    Section · 02

    Skills

    AutomationlmsOpen sourceISOInternshipmetadatacodingPythonSystem DesignMachine Learning

    Python & Generative AI Engineer Professional · waiting for your command