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SKILLESE TECHNOLOGIES

Professional Agentic AI Engineer Internship Program

Build AI That Thinks. Plans. Reasons. Acts.

Learn • Build • Deploy • Intern • Get Hired. The Future Belongs to AI Engineers.

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180 Days Residency 20+ Projects Live Internship QR Checked Certificate
AGENTIC_AI_ENGINEERING ACTIVE COHORT
Orchestrator
LangGraph
Tool Calling
FastAPI Server
Data Protocol
MCP Server
Technology Evolution

The Paradigm Shift in Artificial Intelligence

Artificial Intelligence is rapidly evolving from simple chatbots to autonomous AI systems capable of planning, reasoning, collaborating, and completing complex business tasks.

What Companies Need

Today's companies are hiring professionals who can build AI Agents, Multi-Agent Systems, AI Automation Platforms, Enterprise AI Assistants, RAG Applications, AI Copilots, and Intelligent Business Workflows.

Our Mission

This internship prepares students to become industry-ready Agentic AI Engineers through project-based learning, structured mentorship, and a production-style internship.

Who Should Join?

Ideal for Engineering, MCA, BCA, and MSc Computer Science Students, Fresh Graduates, Software/Python Developers, AI Enthusiasts, and Career Switchers.

Incubator Values

Why Choose Skillese Technologies?

We bridge the gap between traditional learning and production software engineering.

Industry-Oriented Curriculum

Designed using current hiring trends from startups, product companies, and enterprise AI teams.

Learn by Building

Every concept includes Live Coding, Hands-on Labs, Mini Projects, Weekly Projects, and Production Projects.

Internship Experience

Students work on real-world business problems in Agile teams, simulating production tasks.

Portfolio First

Graduate with a GitHub Portfolio, Live Deployments, Technical Documentation, Professional Resumes, and LinkedIn Profiles.

Career Accelerator

Mock Interviews, Resume Building, LinkedIn Optimization, Soft Skills, Freelancing Guidance, and Startup Mentorship.

Tuition Tiers

Program Structure

Select the program duration that matches your current baseline and career goals.

Program Duration Best For
Program 1 45 Days AI Foundations (Python, git, prompting fundamentals)
Program 2 60 Days AI Automation (FastAPI integrations, vector datastores)
Program 3 90 Days Agentic AI Development (LangGraph, CrewAI workflows)
Program 4 180 Days Professional AI Engineer (Enterprise architecture, production scaling)
Tech Stack

Technologies Covered

We train you across every modern tool used by AI engineering teams.

Programming & Core

Python, Git, GitHub, FastAPI, REST APIs, JSON, Docker

Large Language Models

OpenAI GPT models, Claude Anthropic, Google Gemini, Llama, Mistral open source weights

Agent Frameworks

LangGraph state charts, CrewAI agents, OpenAI Agents SDK, AutoGen workflows, LangChain

Enterprise AI Layer

Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), Vector Databases, AI Memory, Tool Calling, Function Calling

Databases

PostgreSQL, MongoDB, Redis caching, ChromaDB, FAISS

Cloud & Deployment

Docker, Railway clusters, Render server, Vercel deployments, Streamlit UI dashboards

Competency Blueprint

Skills You Will Master

We categorize your learning outcomes into 6 core engineering competencies.

AI Foundations

Python coding scripts, complex data structures, REST API architectures, and Git software engineering best practices.

Large Language Models

Prompt Engineering templates, context engineering parameters, function calling payload maps, structured JSON outputs, and AI APIs integration.

Agentic AI

Planning stages, model reasoning, reflection layers, short/long-term memory setups, tool usage schema files, and autonomous workflows.

Multi-Agent Systems

Team AI coordination, agent collaboration channels, dynamic delegation structures, and Supervisor agents managing nodes.

RAG Engineering

Embeddings creation, text chunking heuristics, vector search models, custom knowledge bases, and hybrid semantic/keyword search.

Production AI

Evaluation metrics, automated test pipelines, monitoring traces, model guardrails, security scans, and cost optimization telemetry.

Learning Routine

Daily & Weekly Structured Methodology

Our roadmap runs on a continuous feedback cycle ensuring software engineering principles become second nature.

Every Day:

  • ⚡ Theory Session & Live Coding
  • ⚡ Guided Practice & Hands-on Lab
  • ⚡ Assignment, Daily Quiz, and Code Review

Every Week:

  • ⚡ Coding Challenge & Weekly Assessment
  • ⚡ Mentor Session, Mini Project, and Interview Prep

Every Month:

  • Major capstone project launch
  • Sprint review logs & Demo Day
  • GitHub portfolio sync updates

Internship Daily Sprints:

Sprint Planning Daily Standups Code Reviews Bug Fixing Deployment
Case Studies

12 Production-Ready Projects You Will Build

Real-world operational systems deployed on staging servers.

AI Resume Analyzer

Automated screening pipeline checking resumes and extracting comparative score logs.

AI Career Coach

Conversational roadmap planner evaluating skill cards to draft mock technical review guidelines.

AI Document Assistant

Dynamic file scanner organizing text folders, generating document indexing sheets.

Enterprise RAG Chatbot

Search bot connecting databases and internal manuals to deliver context-backed answers.

AI Customer Support Agent

Multi-agent helper checking histories to compose responses and resolve tickets.

Multi-Agent Research Platform

Autonomous researchers crawling Google Scholar and compiling comparative tables.

AI Meeting Assistant

Audio transcript parser formulating checklist grids and assigning tasks.

AI Recruitment System

OCR profile checker ranking applicant files based on target criteria matches.

AI Coding Assistant

Autonomous codebase checker loops on terminal syntax errors to rewrite code files.

AI CRM Automation

Sync social media leads to CRM databases using webhooks and API layers.

AI Business Dashboard

Interactive visualization cards displaying latency logs and API costs parameters.

Autonomous Business Operations Agent

Autonomous state agent executing daily database operations, reporting on Slack.

Career Acceleration

Job-Ready Deliverables & Support

  • Verified Internship Completion Certificate (containing unique ID & QR checking details)
  • Performance LOR signed by Digiteease Inc. Incubator director
  • Public portfolio website detailing 20+ projects (Program 4)
  • Project completion certificates for major capstone systems
  • ATS-friendly resume formatting & mock system review boards
  • Soft skills: Communication, Client interaction, Problem solving, Teamwork

Why Companies Prefer Skillese Graduates:

Our candidates are trained to build complete AI applications, develop autonomous agent pipelines, integrate databases, deploy production-ready code, and collaborate in Agile developer teams.

Career Opportunities (12 Roles):

AI Engineer Agentic AI Engineer LLM Engineer AI Automation Engineer Prompt Engineer RAG Developer AI Solutions Engineer AI Startup Founder

Enrollment Process

A systematic onboarding pipeline built to prepare candidates for active sprints.

1
Register Online
2
Eligibility Screen
3
Attend Orientation
4
Get Resources
5
Live Training
6
Build Projects
7
Internship
8
Graduate

Frequently Asked Questions

No. Program 1 starts from core Python variable foundations, making it suitable for beginners.
A protocol designed to connect LLM agent systems directly to local databases, file trees, and terminal directories.
Longer programs (Program 3 and 4) incorporate active staging client ticket sprints and team configurations.
Yes. We offer zero-cost EMI plans for all Indian credit card options and selected partner cards.
You can upgrade your track within the first 4 weeks by paying the difference in tuition.
We run asynchronous GitHub checks. Senior developers review your PR line-by-line before approvals.
OpenAI GPT-4o, Anthropic Claude-3.5, and Google Gemini-1.5 multimodal structures.
We issue verified digital credential assets containing QR check links suitable for LinkedIn.
We grant merit scholarships of up to 40% based on our initial coding assessment check.
Career development support focuses on practical project work, portfolio preparation, and interview-readiness guidance.
We offer online self-paced study plans combined with live weekly mentor review sessions.
Review the current refund terms with the admissions team before enrolment.
PostgreSQL relational databases, MongoDB, and vector search stores like ChromaDB and FAISS.
No. Standard systems running VS Code are sufficient since model compute is API-based.
Prompt engineering is one part of the curriculum; practical AI work also involves workflows, tools, testing, and project documentation.
It is an orchestrator designed to route cyclical multi-agent workflows managing state graphs.
We configure Model Context Protocol (MCP) integrations alongside REST webhook structures.
Yes. We check commit message naming guidelines and file structure alignments.
Yes. Write customized Dockerfiles containerizing API codes for cloud deployment.
Simply complete the Quick Apply form below to trigger your syllabus copy details.

Transform Your Career into the
Future of Intelligent Systems

Bypass generic coding mockups. Secure a verified portfolio, deploy LangGraph servers, and start landing developer callbacks.

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Submit your details to check qualification. Our intake sizes are strictly capped to maintain high mentor feedback cycles.

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