AI Engineer Intern (Full-Stack + Agentic AI)
Dobbe AI Verified employer
Actively hiring · Posted 21d ago · JEV2610354EEE1B87
Job description
This internship blends full-stack web development with AI engineering, giving you hands-on experience in building intelligent, LLM-integrated applications. You’ll work on both user-facing features and back-end logic while enabling AI agents to reason and act through tool-based interactions.
Key Responsibilities
Develop and maintain scalable web applications with a focus on usability and performance.
Build responsive front-ends using React.js, and develop back-end APIs with FastAPI.
Implement and expose tools, resources, and prompts using the Model Context Protocol (MCP) to support agentic AI workflows.
Integrate RESTful APIs and WebSockets for real-time front-end and back-end communication.
Build LLM-compatible endpoints and participate in the orchestration of agentic AI use cases (e.g., dynamic tool invocation, context-aware actions).
Collaborate with cross-functional teams including designers and AI/ML developers to integrate AI-driven features.
Contribute to real-time data visualization and analytical dashboards.
Write clean, well-structured, and modular OOP-based code.
Debug and troubleshoot issues across the stack.
Optimize applications for maximum speed, scalability, and LLM performance context.
Required Skills
Front-End: Proficiency in React.js, HTML, CSS, JavaScript.
Back-End: Strong experience with Python (FastAPI preferred), REST APIs, and WebSocket integration.
Agentic AI: Exposure to LLM agents, tool-calling, or LangChain/OpenAI/Claude-based workflows.
MCP: Understanding of the Model Context Protocol or willingness to learn and build MCP-compliant tools and resources.
Concepts: Solid grasp of Object-Oriented Programming (OOP), application routing, JSON-RPC communication, and asynchronous processing.
Databases: Familiarity with SQL (PostgreSQL or MySQL) and/or NoSQL (MongoDB).
Version Control: Experience using Git and GitHub for collaborative development.
Debugging & Testing: Working knowledge of writing testable code and debugging full-stack issues.
Preferred Skills (Good to Have)
Experience with cloud services like AWS, Azure, or Google Cloud.
Exposure to AI/ML libraries (e.g., TensorFlow, PyTorch).
Experience with Docker, CI/CD pipelines, or DevOps practices.
Familiarity with image processing, DICOM files, or healthcare applications.
Who Should Apply?
Students or recent graduates in Computer Science, IT, or related fields.
Enthusiastic learners with a passion for building real-world software applications.
Candidates looking to work with modern tools and frameworks in full-stack development.
What We Offer
Mentorship from industry experts and access to real project codebases.
Opportunity to work on cutting-edge AI-integrated platforms.
Certificate of Internship.
Potential Pre-Placement Offer (PPO) based on performance and team fit.
How to apply
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