AI Engineering for Software Engineers
Sujeet Mishra
AI Engineer & Consultant for F-500 firms
Prasenjit Mukherjee
AI/ML | Search | Ex-Microsoft, Yahoo
An 8-week roadmap for software engineers to become production-ready AI engineers
For software engineers, moving into AI engineering is not just about learning new tools—it’s a mindset shift.
Over the past year, we’ve worked with engineering teams, from Fortune 500 companies to unicorn startups, helping them adopt AI-native and agent-based systems. One pattern shows up repeatedly: engineers don’t struggle because they can’t build, but because AI systems behave very differently from deterministic software.
⚙️ Engineers must learn how to design, evaluate, and operate probabilistic systems, reason about failures and trade-offs, and think end-to-end—from use-case identification to production and scale.
Many engineers hesitate because they believe AI engineering requires deep ML or statistics expertise. In reality, modern AI engineering is about system design, evaluation, observability, and production readiness—skills engineers already have but need to apply in a new context.
🚀 This course provides a practical 8-week roadmap to make that transition by building and extending a real, production-grade agentic system.
By the end, you won’t just understand AI systems—you’ll think and operate like an AI engineer.
For queries, write to us: ai-education@theseuslab.ai
What you’ll learn
By the end of this course, you’ll transition from a software engineer to a confident AI engineer—able to identify the right problems, design
Understand how LLMs work under the hood and why they behave the way they do
Learn best practices for working effectively with LLM-based applications including Task-breakdown and Prompt Engineering
Apply LLM-powered tools (e.g., Cursor, Lovable) across the SDLC to build and ship features faster.
Learn core agent concepts: tool calling, memory, MCP/A2A, Human and Agent coordination
Implement RAG, context engineering, and multi-step agent workflows
Explore modern design patterns, deep agents, and agent skills through hands-on exercises
Learn why evaluation is the backbone of production-grade AI systems
Use Langfuse to trace, observe, and debug agent behavior
Identify failure modes early using metrics, logs, and iterative testing
Learn a simple framework for identifying, validating, and prioritizing AI use cases
Understand the stages of an agentic project: pilot, production, and scaling
Explore real-world challenges teams face when deploying AI inside organizations
Identify a real problem and design an agentic solution from scratch
Build, evaluate, and refine the system with instructor guidance
Finish with a working internal POC or portfolio-ready project
Who this course is for
Software engineers looking to transition into AI engineering roles and build production-grade AI systems
AI engineers and data science professionals
who want to get a hands-on experience of building, evaluating and scaling agentic AI applicationsProduct managers and Tech leaders
seeking a practical, system-level view of how production-ready AI applications are designed and shipped
Prerequisites
Familiarity with Software Engineering Fundamentals
Basic understanding of SDLC concepts like databases, APIs, frontend/backend systems, and servers
Prior Programming Exposure (or Willingness to Ramp Up)
Some programming experience, even if not recent—or willingness to spend ~8 hours pre-course to learn Python (we will provide resources)
Curiosity and Willingness to Experiment
Openness to learning, experimenting, and thinking differently
What's included
Live sessions
Learn directly from Sujeet Mishra & Prasenjit Mukherjee in a real-time, interactive format.
On-demand 1-1 Instructor Connect
Connect with instructors 1-1 (beyond live sessions) to unblock yourself and get personalized attention
21 Assignments, with personalized feedback
On design & architecture and code quality
Capstone Project
Build how enterprises build real applications—from use-case identification through development and evaluation to production
Community of peers
Stay accountable and share insights with like-minded professionals
Lifetime access
Unlimited access to all course content and recordings, even after the course ends.
Certificate of Completion
Share your credentials on LinkedIn
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund through the second week of the course.
Course syllabus
16 live sessions • 44 lessons • 15 projects
Week 1
Feb
18
Welcome & Course Kick-off
Modern AI: Landscape and LLM Fundamentals
Engineering Productivity with LLMs Across the SDLC
Feb
22
[Live] Discussion of Week-1 Content and Exercises
Week 2
Get started with building Agentic Applications
Give Agents the ability to Act in the real-world
Feb
26
[Live] On-Demand 1-1 Instructor Connect
Feb
28
[Live] Discussion of Week-2 Content and Exercises
Schedule
Live sessions
2 hrs / week
1. Live lessons - Saturday, 11:00 AM - 12:30 PM EST 2. On-demand 1-1 Instructor connect - pick your slot on Thursday between 11:00 AM - 12:30 PM EST
Wed, Feb 18
4:00 PM—5:30 PM (UTC)
Sun, Feb 22
4:00 PM—5:30 PM (UTC)
Thu, Feb 26
4:00 PM—5:30 PM (UTC)
Projects
2-4 hrs / week
Assignments & Capstone Project
Async content
2-3 hrs / week
Testimonials
The GenAI training was very useful and easy to follow. I learned about important concepts like RAG (Retrieval-Augmented Generation), embeddings, and how to use frameworks like LangChain and LangGraph to build AI workflows. The hands-on examples helped me understand how these tools work together to create powerful solutions. Overall, it was a great learning experience that will help me apply AI in real projects.
Aditya V.
Technical Associate @ GSKSujeet delivered an AI workshop for our team. It was very well structured and effectively covered all key aspects highlighting the importance of AI in our function. It included relevant use cases and introduced basic AI tools being adopted by other retail organizations. Overall, a big shout-out and thank you to team Theseus for conducting such an insightful and engaging workshop for us
Saurabh S Sawhney
Head Learning & Development at BATA (Bata Training Academy)Sujeet delivered an AI session for our team at Medi Assist. The session broadened our understanding of the AI landscape and gave us an overview of how we can leverage AI in different sub-functions. The session was appreciated by all the team members.
Pradeep Gulati
CHRBP @ Medi AssistI enjoyed the trainer’s clear explanations, practical code examples, and the latest tech trends they shared.
Natalia R.
Technical Associate @ GSKThe Agentic AI workshop covered a lot of ground and helped us understand the nuances of running systems successfully in production
Abhigyan Shivam
Sr. Data Scientist @ AkamaiThe session conducted by Sujeet gave us a clear, hands-on understanding of RAG systems and how to evaluate them effectively in real-world scenarios
Rishu Kumar Mishra
Data Scientist @ A.P. Moller - Maersk
Frequently asked questions
A Course by Theseus AI Lab
Theseus AI Lab - Helping organizations cross the 0 → 1 AI threshold successfully. we partner with Fortune 500 enterprises, high-growth unicorns and science-driven startups globally, guiding them from strategy through to scalable AI success.
We offer AI consultation, implementation and custom AI trainings tailored to organizations. Contact us - ai-education@theseuslab.ai
Client Testimonials
Us In Action
$999
USD