IT Infrastructure
Datacentre & Critical Facilities
The physical layer. Unfashionable, non-optional, and being rebuilt right now because AI broke the assumptions it was designed around.
Seventy-three percent of IT infrastructure postings name datacentre or colocation work and 70% name power, cooling or critical facilities. This is not a legacy field — it is a constrained one, and the constraint has become the story: AI workloads need power densities that most existing halls physically cannot deliver.
| Time | What you are actually doing |
|---|---|
| 07:30 | Walk the floor. Thermal imaging on a suspect rack, a check on a PDU that alarmed overnight, and a look at the cage where the new row is going. |
| 09:30 | Capacity meeting. Not server capacity — power. How many kilowatts are contracted, how many are committed, and how many are actually drawn, because those three numbers are always different. |
| 11:00 | A cooling design review. Rear-door heat exchangers versus direct-to-chip for the new deployment, and whether the building's water loop can carry it. |
| 14:00 | Vendor and logistics. Lead times, a delayed shipment, and the fact that the row cannot energise until a specific part arrives. |
| 16:00 | Change control. A UPS maintenance bypass next weekend, which is the highest-risk routine activity in the building and is planned accordingly. |
What makes this hard
- Nothing is reversible quickly. A software mistake rolls back; a power design that cannot carry the load is a construction project.
- Lead times dominate. Transformers, switchgear and generators are measured in quarters, sometimes years, so capacity planning has a horizon most technologists never work at.
- Concurrent maintainability — every component must be serviceable without taking load offline, which is what Tier III actually means and why it costs what it does.
- Safety is a real constraint, not a compliance checkbox. Arc flash, working at height, and lockout-tagout are the parts of infrastructure where people are genuinely hurt.
The decisive round
“We want to deploy AI training in an existing hall. Can we?”
Interviewer: “The business wants to put GPU training racks into our existing datacentre. What do you tell them?”
A weak answer. “I'd check we have the space and power available, and if not we'd need to look at expanding or using a colocation provider.” Right conclusion, no reasoning, and it misses the constraint that actually decides it.
A strong answer. “Space is almost never the binding constraint, and I would say that first. A hall designed for 5 to 10 kW per rack has the floor area for GPU racks and cannot power or cool them — a dense training rack can draw 40 to over 100 kW, so a single row can exceed what a whole aisle was designed for.
So the questions in order. What is our contracted power and our actual draw? The gap is what is genuinely available, and it is usually smaller than people assume because commitments are counted optimistically. What can the distribution deliver to a single rack position? Even with headroom in the building, the busway, PDUs and branch circuits to that spot may cap far lower. Can we reject the heat? This is where it usually fails — air cooling runs out somewhere around 30 kW per rack in most designs, so we are talking about rear-door heat exchangers or direct-to-chip liquid, which needs a water loop the building may not have. Can the floor carry it? Dense racks are heavy, and raised floors have limits.
Then the honest answer, which is usually: we can deploy a small number of racks by spreading them across the hall to distribute thermal load — which wastes space and is often the right pragmatic move — and anything at scale needs either a retrofit with liquid cooling or a purpose-built facility. I would give the business both the number of racks we can take today and the lead time and cost for each option, because ‘no’ without alternatives just gets routed around.”
Knowing that power and heat rejection bind before space, and giving the business a number they can plan against rather than a refusal.
- Learn the arithmetic: kW per rack, PUE, cooling capacity, and how to convert a GPU specification into a power and heat budget.
- Understand redundancy notation — N, N+1, 2N, and what concurrently maintainable actually requires.
- Know the liquid cooling options and their building implications, because this is the live question in the field right now.
- Have a capacity story where you forecast a constraint far enough ahead that something could be done about it.
Compensation
| Market | Band | Notes |
|---|---|---|
| United States | $95k – $185k | Critical facilities engineering with electrical depth sits at the top |
| India | ₹8L – ₹35L total | Growing quickly with domestic datacentre buildout |
| Both | — | The lowest band of the five fields, and the one with the least competition per posting |
The book for this field
Networks, Automation, Connectivity & Data Centres
Twelve chapters from a single packet to a submarine cable. Subnetting worked by hand, BGP and why hijacks succeed, DNS and the two outages worth knowing by name, TLS and the expiry that still takes down companies, cloud networking with the arithmetic, transit and peering, colocation and what an AI rack did to the industry, and four debugging scenarios worked end to end.
All 18 chapters in Networks, Automation, Connectivity & Data Centres →
Also read for this role
Infrastructure & Reliability
Reliability and error budgets, capacity arithmetic, networks, storage and the restore you have not tested, the physical layer, a debugging method that transfers, running production, and an honest look at Kubernetes. Plus a Middleware section — web and application servers, messaging (IBM MQ, Kafka) and managed file transfer, from basics to licensing and cost.
Cross-cutting
Skills every archetype tests
These are shared across every field on this site — the same question asked in different vocabulary — so preparation here compounds rather than being spent once. The book above is specific to your field.
Practice the 8 IT Infra questions → · Back to IT Infrastructure →