Applied AI - The new role
Technically it's not a new role, however it's new compared to other software roles. If you are in an engineering college then this term is totally relevant for you.
Software industry is evolving and as a software engineer myself, I can say that I don't write software the way I used to do in 2020. Actually... I don't write code at all. Claude and Codex write code for me, push it, make sure it deploys which I sip my coffee with friends.
The transition to this stage wash't quick. Initially, with augment of LLMs and us starting to use it in our daily tasks, we stopped going through code solutions on stackoverflow since ChatGPT could generate me the solution within an instant.
That was the early phase... Just search being transformed.
Within an year, I started using AI Coding Tools such as Cursor and replaced my VSCode paired with Copilot / Tab9 that was just for autocompletion. Now AI was writing code and I was reviewing.
Within next few months, the coding tools evolved and I realised I can trust them with even larger tasks. AI creating a feature end to end and then creating a PR for it. That became possible.
Next, we started using the word Agent. We wanted LLMs to behave like a person responsible for one thing. Many such people taking responsibility of their own stuff and collaborating together like a team. That's multi-agents. Agents are configurable. Agents can have their own skills. Agents can invoke other agents. A lot of things can be done with Agents.
So I have an agent which applies for jobs, another agent watches the email and replies to the job specific emails, another agent creates cover letters, another agent converts my generic resume to job specific ones to apply for different roles.
Next, we started working with Agents on cloud. With Codex, you can ask it from your laptop or phone from anywhere in the world to fix a bug and create a pr for the bug fix and request the reviewer agent to review it and merge it.
Isn't this awesome?
Companies now don't need people who are good at writing code. That's been delegated to AI. Companies now look for people who can build systems at a higher level. They look for people who can collaborate with AI to build AI.
This role needs sufficient depth of knowledge for building systems as well as knowledge of how efficient AI systems work. That's the role we are talking about. Let's redefine it in better words.
What is Applied AI (Applied AI Engineer role)
An Applied AI Engineer is a software engineer who uses existing AI models (especially large language models like GPT, Claude, Gemini, and open-source models) to build real-world products and business solutions.
Why this role was needed?
This role sits at the intersection of AI roles and software development. It's a "jack of all" role where you don't need deep expertise in AI. You don't need to understand the very basics of AI. You also don't need to learn a specific programming language and get expert at it.
All you need is to understand how to build with AI, how to scale with AI, and how to think in terms of architecture. Unlike AI researchers, who create new algorithms and train novel models, applied AI engineers focus on making AI useful in practice.
What an Applied AI Engineer Does
Typical responsibilities include:
Building AI-powered applications and agents
Integrating AI models through APIs
Designing prompts and workflows
Implementing Retrieval-Augmented Generation (RAG)
Connecting AI to databases, tools, and external systems
Evaluating and improving AI performance
Deploying and monitoring AI systems in production
Why is this role relevant for you?
In 2026, almost everyone is using AI to write code. I myself don't read my code unless in reviews. AI writes my entire stack, manages my AWS and GCP and other platforms via CLI.
If you are in college, you will be learning basics of software engineering. But none of you will be writing code yourself for all your projects. Because AI has never been so much accessible as it is now.
So in such environment, an obvious career path is the one where you use AI to do heavy uplifting while you handle the higher level architectural decisions. That's what Applied AI Engineering is.
In coming blogs, we will be discussing about becoming an Applied AI Engineer in detail and also create some projects.
That's it.