The AI is only useful to a client if their people can reach it and if it stays standing. That's your role. You build the applications the client's people actually touch, the copilots and tools that carry our AI work, and you build and run the platform we deliver and operate those systems on. When our work reaches a client's users, it reaches them through your work.
There are two sides to it, and I want to be honest that they're both substantial. On one side, application: clean, fast, well-built software the client's people use in their day and don't have to think about. On the other, platform: the containers, orchestration, cloud, and observability that keep what we deliver reliable and let us see what it's doing, across engagements. The thread between them is the same one that runs through everything here. A demo is easy. Something a client depends on is not, and that's the bar.
The work:
- Build the front ends and application backends for the copilots and tools we deliver to clients
- Design and run the delivery platform: containerization, orchestration, and cloud infrastructure
- Own CI/CD and the platform observability stack so we ship safely and see problems before the client does
- Structure services sensibly so each system stays understandable as it grows and hands over cleanly
- Keep performance, cost, and security of the platform as first-class concerns, not afterthoughts
Where your work ends. You own the surface and the platform: the applications people use and the infrastructure everything runs on. You don't build the data foundation (Data Engineer), the models (Data Scientist), or what happens inside the models in production (AI Engineer). You provide the reliable ground the other three build and operate on, and the interface the client's people meet.
What success looks like:
- The client's people use what you build without friction or training wheels
- The platform stays up and shows what it's doing
- We ship safely and often, because CI/CD and observability make it safe to
- What we deliver can be understood and, when the client wants it, handed over to their own team
The stack we work in today: React, Next.js, and TypeScript on the front end; Python and FastAPI on the application backend; Docker for containerization, Kubernetes for orchestration, and AWS, GCP, or Azure underneath; a microservices approach where it fits; CI/CD pipelines; and observability with ELK, Prometheus, and Grafana. You don't have to arrive knowing every one of these. What you do need is the shared foundation: real software discipline, systems thinking, and enough MLOps awareness to operate what you build and work well with the people whose models run on your platform. You won't own the model lifecycle, but you'll make it possible. In consulting you'll often work close to the client's own engineers, so building things they can understand and take over is part of doing the job well.
About The Strong AI, and how we work
The Strong AI is an end-to-end AI implementation partner. Clients come to us because most organizations can run an AI experiment, but few can turn it into a system their business depends on. We close that gap. We don't hand over slideware or a notebook; we build systems that work inside a client's business, and where they want it, we run them.
You'll work across engagements and industries, on different problems and often different stacks. We're technology-agnostic: the problem and the client's environment choose the tools, so treat any stack we list as the ground we work on today, not a gate.
Across all roles, we ask for the same way of working:
- Real software. Tested, reviewed, versioned code the next person, or the client's team, can pick up.
- MLOps mindset. A model's life starts at deployment. Monitoring, retraining, drift, and rollback are handled before anything breaks.
- Systems thinking. You see both the value slice and the whole it compounds into.
- Quality and security, owned by you. Designed in from the first decision, not inspected in at the end. Everyone builds to the highest standard.
- Built for handover. Clear code and docs the client's own team can understand, operate, and take over.
Pay: ₹500,000.00 - ₹1,000,000.00 per year
Benefits:
- Flexible schedule
- Work from home
Application Question(s):
- What interests you (in your own words) about working for The Strong AI?
Work Location: Remote