Agentic AI Mastery Program for Software Engineers 2026

Applied Agentic AI for Software Engineers

Build and run production-grade agentic AI systems used by top engineering teams across real-world use cases.

Built for software engineers who want to own agentic systems end to end, not just experiment with GenAI tools.

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Program Overview

Who This Is Built For

Program Duration

Live Learning

Projects

Instructors

What You’ll Build and Learn

Systems-First Capstone Architecture

Agentic AI Interview Preparation

Careers transformed

25k+

Average package for alumni

$312,275

Average ROI on course price

5x

30+ Tools & Tech You’ll Learn

Why SWEs Choose This Applied Agentic AI Program

Built for Real Production Systems

What SWEs Actually Build at Work

Designed Specifically for Software Engineers

Learn from Engineers Building It Today

Hands-On, Production-Style Projects

Results Engineers Trust

This is a living curriculum, continuously updated to reflect how agentic AI systems are built and operated in 2026 and beyond.

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Detailed Curriculum: Applied Agentic AI for SWEs

Applied Agentic AI Core for SWEs Agentic AI System Design and Interview Preparation for SWEs (Weeks 11–17) AI SDE-Specific Career Guidance & 1:1 Mentoring Bonus Content: Self-Paced

Applied Agentic AI Core for SWEs

Week 0: Foundations and Environment Setup

Outcome: Set up the stack and ship a working agent.

Week 1: Agentic Foundations and Reflex Agents

Outcome: Design predictable and controllable agents.

Week 2: RAG-Powered Knowledge Agents

Outcome: Build reliable, retrieval-backed agents.

Week 3: Multi-Agent Systems

Outcome: Design coordinated multi-agent workflows.

Week 4: Conversational and Multimodal Agents

Outcome: Build stateful conversational agents.

Week 5: Agent Communication Protocols

Outcome: Design structured, debuggable agent communication.

Week 6: Domain-Specific and Vertical Agents

Outcome: Build production-ready domain agents.

Week 7: Summarization and Recommendation Systems

Outcome: Ship agents that support real decisions.

Week 8: Safety, Evaluation, and Cost Control

Outcome: Operate agents safely and efficiently.

Week 9: Fine-Tuning and Model Integration

Outcome: Integrate custom models responsibly.

Week 10: Enterprise Capstone System

Outcome: Design a production-grade agentic AI platform.

Agentic AI System Design and Interview Preparation for SWEs (Weeks 11–17)

Weeks 11–12: Agentic System Design Patterns

Outcome: Explain system design choices clearly in interviews.

Weeks 13–14: Orchestration, Memory, and Data

Outcome: Defend orchestration and data decisions confidently.

Weeks 15–17: Evaluation, Safety, and Production Readiness

Outcome: Handle senior SWE interviews focused on production AI systems.

AI SDE-Specific Career Guidance & 1:1 Mentoring

AI SDE-Specific Career Guidance & 1:1 Mentoring

Foundational Materials

Python Fundamentals Refresher

Evolution of GenAI

Hands-on with Generative AI Models

ML Foundations

Specialized Sessions

Laying the Groundwork for AI-Driven Development

Building Effective Prompts and Configuration-Driven Apps

Innovating with Multi-Agent Systems and Specialized Models

Harnessing LLM Frameworks for Real-World Development

From Development to Deployment: Scaling and Debugging AI Models

Detailed Curriculum: Applied Agentic AI for SWEs

Applied Agentic AI Core for SWEs Agentic AI System Design and Interview Preparation for SWEs (Weeks 11–17)

Applied Agentic AI Core for SWEs

Week 0: Foundations and Environment Setup

Outcome: Set up the stack and ship a working agent.

Week 1: Agentic Foundations and Reflex Agents

Outcome: Design predictable and controllable agents.

Week 2: RAG-Powered Knowledge Agents

Outcome: Build reliable, retrieval-backed agents.

Week 3: Multi-Agent Systems

Outcome: Design coordinated multi-agent workflows.

Week 4: Conversational and Multimodal Agents

Outcome: Build stateful conversational agents.

Week 5: Agent Communication Protocols

Outcome: Design structured, debuggable agent communication.

Week 6: Domain-Specific and Vertical Agents

Outcome: Build production-ready domain agents.

Week 7: Summarization and Recommendation Systems

Outcome: Ship agents that support real decisions.

Week 8: Safety, Evaluation, and Cost Control

Outcome: Operate agents safely and efficiently.

Week 9: Fine-Tuning and Model Integration

Outcome: Integrate custom models responsibly.

Week 10: Enterprise Capstone System

Outcome: Design a production-grade agentic AI platform.

Agentic AI System Design and Interview Preparation for SWEs (Weeks 11–17)

Weeks 11–12: Agentic System Design Patterns

Outcome: Explain system design choices clearly in interviews.

Weeks 13–14: Orchestration, Memory, and Data

Outcome: Defend orchestration and data decisions confidently.

Weeks 15–17: Evaluation, Safety, and Production Readiness

Outcome: Handle senior SWE interviews focused on production AI systems.

Live Guided Projects

First LLM-powered Agent Knowledge Assistant (RAG with Evaluation) Multi-Agent Research Team Conversational Research Assistant Negotiation Simulator Price Comparison Agent Decision Support Agent Production-Ready Support Agent Domain-Specific Fine-Tuned Agent

First LLM-powered Agent

Knowledge Assistant (RAG with Evaluation)

Multi-Agent Research Team

Conversational Research Assistant

Negotiation Simulator

Price Comparison Agent

Decision Support Agent

Production-Ready Support Agent

Domain-Specific Fine-Tuned Agent

Projects are subject to change as per industry inputs.

Live Guided Projects

First LLM-powered Agent

Knowledge Assistant (RAG with Evaluation)

Multi-Agent Research Team

Conversational Research Assistant

Negotiation Simulator

Price Comparison Agent

Decision Support Agent

Production-Ready Support Agent

Domain-Specific Fine-Tuned Agent

Projects are subject to change as per industry inputs.

Production-Grade Capstone Projects for Agentic AI Engineers

Capstones stay aligned with industry needs. Pick from 10 production-grade projects or build your own system.

AI Finance Assistant AI Content Marketing Assistant AI Call Center Assistant AI-Powered Email Assistant AI-Powered DevOps Assistant AI-Powered Patient Assistant (Healthcare) AI-Powered Security Auditor AI-Driven Legal Document Analyzer AI Supply Chain Optimization Assistant Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs Resume/ATS scoring assistant BYOP [Bring Your Own Project]

AI Finance Assistant

Build a personalized financial education experience with an AI-powered Finance Assistant that leverages multi-agent LLM systems and Retrieval-Augmented Generation (RAG). The assistant delivers context-aware investment guidance, real-time market insights, and portfolio analysis tailored to each user. Designed for scale, it simplifies complex financial concepts and empowers beginners to make informed decisions.

AI Content Marketing Assistant

Accelerate marketing efforts with ContentAlchemy, an AI-powered content creation platform that leverages multi-agent LLM systems to generate high-quality blogs, LinkedIn posts, visuals, and research-driven content. The system uses intelligent agent orchestration to ensure SEO optimization, brand voice consistency, and platform-specific formatting. Designed for creators and businesses, it enables scalable, on-demand content production across multiple formats and channels.

AI Call Center Assistant

Transform raw call data into actionable insights with an AI-powered Voice-to-Insights system that leverages multi-agent LLMs and speech-to-text technology. The system automatically transcribes, summarizes, and quality-checks support calls, providing structured evaluations and key takeaways at scale. Designed for modern call centers, it standardizes QA processes, improves compliance, and enables faster, data-driven decision-making.

AI-Powered Email Assistant

Streamline communication with an AI-powered Email Assistant that uses multi-agent LLM workflows to generate personalized, context-aware email drafts. The system intelligently detects intent, applies custom tone styling, and ensures high-quality output through review and validation agents. Built for productivity and scalability, it enables teams to draft professional emails in seconds while maintaining consistent voice and messaging.

AI-Powered DevOps Assistant

Build an agentic system that automates DevOps workflows through four specialized agents: a Code Analyzer for security reviews, a CI/CD Monitor for deployment oversight, an Infrastructure Scaler for resource management, and an Incident Resolver for system diagnostics. Build it with LangChain, CrewAI, and OpenAI API and integrate with GitHub Actions, AWS Lambda, and containerization tools, while using vector databases and monitoring solutions.

AI-Powered Patient Assistant (Healthcare)

Build an assistant that streamlines healthcare services through four specialized agents: a Symptom Checker for initial assessments, an Appointment Scheduler for EHR/EMR integration, a Medical FAQ Bot for patient queries, and an Insurance Advisor for claims guidance. Use LangChain, GPT-4, and healthcare APIs to create a system that offers comprehensive patient support while maintaining secure data management through VectorDB storage.

AI-Powered Security Auditor

Build a comprehensive agentic system utilizing four specialized agents to protect applications: a Vulnerability Scanner for detecting common threats, a Code Security Analyzer for OWASP Top 10 compliance, a Log Analyzer for anomaly detection, and a Compliance Checker for regulatory standards. Use tools like LangChain, OpenAI GPT, and OWASP ZAP to ensure robust security through integrated monitoring and analysis.

AI-Driven Legal Document Analyzer

Employ four specialized agents to streamline legal document processing: a Contract Analyzer for extracting key elements, a Compliance Checker for regulatory validation, a Case Law Researcher for finding precedents, and a Summary Generator for creating digestible content. Use LangChain, OpenAI, and OCR tools to offer comprehensive legal document analysis through an interactive interface.

AI Supply Chain Optimization Assistant

Build a multi-agent system designed to automate supply chain processes, including inventory management, demand forecasting, and logistics tracking. The system consists of four agents: a demand forecaster using time-series ML models, an inventory manager analyzing stock levels, a logistics tracker monitoring shipments, and a procurement assistant optimizing supplier contracts. Leverage Python, TensorFlow, XGBoost, LangChain, OpenAI API, SQL/NoSQL databases, and visualization tools like Streamlit in this project.

Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs

Enhance software development with an AI-powered pull request (PR) reviewer bot that automates code reviews using Large Language Models (LLMs). This bot provides detailed feedback, identifies bugs, security vulnerabilities, and coding violations, and suggests best practices to streamline the code review process. It improves efficiency and code quality while assisting human reviewers. Integrate with GitHub/GitLab for seamless operation and use models like GPT-4 or Hugging Face Transformers for accurate code analysis. Build with React or Streamlit, and deploy using Docker and AWS for smooth execution.

Resume/ATS scoring assistant

Streamline the hiring process with an AI-powered assistant that automates resume screening and scoring using large language models (LLMs). This tool evaluates resumes against job descriptions, identifying strengths, weaknesses, and alignment with role requirements. It enhances ATS platforms by providing actionable feedback and recommendations to find the best-fit candidates. Integrate with tools like GPT-4, Gemini Pro, and LangChain for seamless operation. Build a user-friendly interface using React, Node.js, and MongoDB, and deploy it on the cloud with Docker and AWS.

BYOP [Bring Your Own Project]

Work on personal or professional projects of your choice. BYOP offers mentorship, structured guidance, and feedback to ensure projects are aligned with industry standards and best practices. It fosters creativity, innovation, and real-world problem-solving, enabling participants to build impactful solutions. You will receive guidance on selecting the right tools and frameworks based on project requirements.

Production-Grade Capstone Projects for Agentic AI Engineers

AI Finance Assistant

AI Content Marketing Assistant

AI Call Center Assistant

AI-Powered Email Assistant

AI-Powered DevOps Assistant

AI-Powered Patient Assistant (Healthcare)

AI-Powered Security Auditor

AI-Driven Legal Document Analyzer

AI Supply Chain Optimization Assistant

Automated Code Reviewer/Pull Request Reviewer Bot Powered by LLMs

Resume/ATS scoring assistant

BYOP [Bring Your Own Project]

Projects are subject to change as per industry inputs. Choose from one of 10 Capstone Projects.

FAANG+ Instructors to Train You

Get mentored by AI/ML leaders who are driving Agentic AI innovation at top global companies.

Ralph Blanes

Research Software Engineer

Rishabh Misra

Lead ML Engineer & Researcher

Ram Vegiraju

ML Architect @ AWS

Samwel Emmanuel

Data & AI Solutions Architect @ Databricks

Ralph Blanes

Research Software Engineer

Rishabh Misra

Lead ML Engineer & Researcher

Ram Vegiraju

ML Architect @ AWS

Samwel Emmanuel

Data & AI Solutions Architect @ Databricks

Ralph Blanes

Research Software Engineer

Rishabh Misra

Lead ML Engineer & Researcher

Ram Vegiraju

ML Architect @ AWS

Samwel Emmanuel

Data & AI Solutions Architect @ Databricks

Assess Your Fit\ \ Free AI Career Session

The IK Experience: What Our Alumni Are Saying

Our engineers land high-paying and rewarding offers from the biggest tech companies, including Facebook, Google, Microsoft, Apple, Amazon, Tesla, and Netflix.

Abhishek Singh

Senior Data Analyst, Jeavio

IK is a GOD-Send to me. If you are looking to upskill or transition in your career, IK is the place to be. I joined Data Science Switchup in November-23 and I am loving the 360 degree experience which IK provides. The instructors are professionals who are currently working in the tier-1 companies so the classes have loads of real-life snippets of their experience which adds true value to students like us. The mock sessions and technical sessions helped me immensely to understand the topic at a deeper level. The Ops Team & Success Coaches are superstars who act like a true friend when you need any sort of assistance.

Dwaraknath Bakshi

Senior Director of Engineering, Freshworks

IK has been an integral part of my life for last seven years. Since being part of some of the early batches to most recently pursuing their ML track I have done several courses with them. What amazes me is the approachability of the staff, the proactive support team and professionalism. The material is amazing and profound. Omkar and Niloy to name a few they have amazing faculty who are very knowledgeable and are also great teachers. I can keep raving about IK. It’s definitely a boon to software engineers.

Venkatesh Babu

Senior Director - ISV/SolEx Technical Partner Management

I highly recommend the Applied GenAI course by Interview Kickstart. The PM path was incredibly well-organized, reshaping my thinking on how to leverage Generative AI in product management. The hands-on approach, insightful curriculum, and experienced instructors made it an outstanding learning experience!

Amit Vaswani

Lead Software Engineer, Highnote

I recently completed the Applied Gen AI course at Interview Kickstart, and I couldn't be more impressed. The course was well-structured into modules, making complex concepts easier to digest. For someone without a strong programming background, I appreciated the beginner Python class they offer for non-programmers—it helped build a solid foundation. The instructors are fantastic and always go the extra mile to ensure every question is answered. They are patient and don’t rush through the material, often allowing classes to run over to ensure everyone fully grasps the concepts. One of my favorite features is the 'Expert Connect,' where you can have 1-on-1 sessions with instructors to clear any doubts. Overall, Interview Kickstart provided an exceptional learning experience, and I highly recommend it to anyone looking to uplevel in their career.

Abhishek Singh

Senior Data Analyst, Jeavio

Dwaraknath Bakshi

Senior Director of Engineering, Freshworks

Venkatesh Babu

Senior Director - ISV/SolEx Technical Partner Management

Amit Vaswani

Lead Software Engineer, Highnote

Assess Your Fit\ \ Free AI Career Session

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Select a course based on your goals

Agentic AI

Learn to build AI agents to automate your repetitive workflows

Switch to AI/ML

Upskill yourself with AI and Machine learning skills

Interview Prep

Prepare for the toughest interviews with FAANG+ mentorship

FAQs

1

What is Agentic AI, and how is it different from traditional AI?

Agentic AI focuses on autonomous systems that operate proactively to achieve goals using LLMs and other tools, without constant human intervention. Unlike traditional AI, which is often reactive and generally requires explicit instructions for each task, Agentic AI understands its environment, thinks through the goals and how to achieve them, makes decisions, takes actions, learns from its experiences, and adapts its behavior over time.

2

What are the practical applications of Agentic AI?

Applications of Agentic AI include:

3

Do I need prior AI or ML experience to enroll in this course?

No, prior AI/ML experience isn’t mandatory. However, a strong foundation in software engineering and familiarity with Python/other coding languages are expected. We start with essentials before progressing to advanced Agentic AI concepts.

4

What kind of projects will I build in the course?

You’ll build hands-on projects like a Financial Bot, Conversational Audio Bot, and choose from 10+ Capstone options (e.g.,Finance Assistant, AI Call Center Assistant, Email Generator). These simulate real-world AI use cases and help build a portfolio for job applications.

5

How do Capstone Projects help my career?

Capstone Projects are designed with FAANG+ hiring managers in mind. Over 67% of hiring managers now demand to see practical know-how rather than certification or theoretical understanding. They’re reviewed for scalability, robustness, and relevance—showcasing your readiness for AI-enhanced software roles.

6

Can I bring my own project?

Absolutely. With BYOP, you can work on your unique project idea with mentor guidance, ensuring it aligns with industry best practices and makes your portfolio stand out.

7

How does this course help me land a FAANG+ job?

Through live sessions led by FAANG+ practitioners, FAANG-focused interview prep, and mock interviews with hiring managers and tech leads. You’ll also build a compelling portfolio with capstone projects reviewed by mentors from companies like Google, Amazon, and Meta.

8

How much time do I need to commit weekly?

Expect around 8 hours of learning per week. This includes 60+ hours of live sessions, 30+ hours of guided project work, and 21+ hours of specialized sessions over 15 weeks. Bonus content and interview prep sessions are available for those who want to go deeper.

9

Who are the instructors?

All our instructors are current or former FAANG+ professionals with deep expertise in Generative AI, LLMs, and AI/ML.

10

What tech stack and tools will I learn?

You’ll work with 30+ industry tools including LangChain, CrewAI, LlamaIndex, Hugging Face, OpenAI APIs, LangGraph, Streamlit, Docker, and Kubernetes—tools widely used in modern AI workflows.

11

Is the course live or self-paced?

It’s a hybrid format, with weekly live expert-led sessions for core learning and projects, plus self-paced bonus content and career prep modules to support flexible schedules.

12

How is this different from a typical ML bootcamp?

This course is domain-specific for software engineers—not a generic AI training or prompt engineering course. It focuses specifically on building real-world agentic systems, integrating LLMs with production environments, and preparing for AI software engineering roles, not just research.

13

What support do I get during the course?

You get access to 1:1 mentoring, career coaching, resume reviews, and mock interviews. Plus, there’s ongoing support from teaching assistants, technical coaches, and peer communities.

14

What are the career outcomes or placement support offered?

Past learners have landed roles with average packages of over $312K. Our career team offers job targeting strategies, referrals, and personalized application help to support your transition.

15

What happens if I miss a live session?

All live sessions are recorded and accessible on-demand. You can catch up anytime and even rewatch for revision.

16

Is there a payment plan?

Yes! We offer multiple financing options to make the course more accessible to working professionals.

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