We run Dataford, an interview prep platform. People come to us to study for specific companies and specific roles before they ever sit in the interview. That gives us a clear view of where the market is heading.

We do not see who got hired. We see who is getting ready. And what people get ready for tends to move before the hiring data does.

Between January and June 2026, more than 200,000 candidates ran over 231k sessions on Dataford. We looked at which companies they studied for, which roles they targeted, and at what level. Here is what we got for you.

By the way, this is candidate behavior on one platform, not a hiring census, so please treat it as an early read, not the universal truth.

The five things worth knowing

If you only read one section, I'd recommend to read this one.

1. Nvidia is the most studied-for company by a wide margin, and the AI labs now sit right next to Big Tech at the top.
2. Software Engineer is still the top role, taking over 22% of all roles.
3. AI Engineer is now the #2 role overall. It passed Data Analyst, Data Engineer, and Data Scientist this year. Individually.
4. Classic data titles are sliding in share while anything labeled AI is gaining a lot of traction.
5. A new batch of AI-native titles showed up mid-year that were basically nonexistent in the beginning of the year.

Now that you got the TLDR.
Let's get into more details.

What are the top companies hiring today

Nvidia is number one, and not by a little. Here is the top 15 by prep volume.

Look at the top eight. A few years ago that block was only FAANG. Now Nvidia leads it, and OpenAI, Databricks, and Anthropic are all sitting in there. Anduril, a defense company, is in the top eight too. You probably heard that terms MANGOS (Meta, Anthropic, Nvidia, Google, OpenAI, SpaceX).

Well this is happening!

The AI labs are becoming the new hot sector

The AI labs are tiny compared to the banks and the consultancies by raw employee count. But what's insane, it's that as a group they still pull more prep than all of consulting.

People are chasing the companies they think are building the future and AI labs are definitely one of them in 2026. Defense is also growing led by Anduril whereas Lockheed Martin, Northrop Grumman are losing ground.

Software Engineer Role is still leading the pack

Before we get to the AI story, software Engineer is still the king, accounting fo 22% of every single prep session on the platform.

If you stack up everything in the engineering family, it is 55% of demand. More than half of all candidates are aiming at some flavor of engineering roles.

AI Engineer is the hottest role in the market

AI Engineer is the #2 role on the entire platform. It now pulls more prep than Data Scientist, more than Data Analyst, and more than Data Engineer. Not combined. Each one, on its own.

AI Engineer       5,007  ████████████████████
Data Analyst      3,858  ███████████████
Data Engineer     3,838  ███████████████
Data Scientist    3,791  ███████████████
ML Engineer       1,784  ███████

Two years ago "AI Engineer" was barely a real job title. Now it is second only to the most generic engineering role there is. That is a fast climb.

What is gaining share (the new hottest roles)

Across the first half versus the second half of the year, here is what moved, measured in points of share so that overall traffic growth does not fake a trend.

Gaining share

• Software Engineer: +3.4
• Research Scientist: +1.2
• AI Engineer: +0.9
• Embedded Engineer: +0.9
• Operations Manager: +0.9
• Account Executive: +0.8
• Data Engineer: +0.6

Losing share

• Product Manager: -0.6
• QA Engineer: -0.6
• Machine Learning Engineer: -2.6
• Data Scientist: -3.1
• Data Analyst: -4.7

The takeaway is not "data is dead." There is still huge demand for analysts and scientists. The energy is just relocating to roles with AI in the name, and the fastest bridge from analytics to that energy is short.

Job titles that did not exist and are popping in H2' 2026

This was our favorite thing in the dataset. A cluster of roles appeared in the second half of the year that were essentially zero at the start of it.

• Forward Deployed Engineer: 229
• GenAI Engineer: 215
• Agentic AI Engineer: 125
• AI/ML Analyst: 82
• AI Research Scientist: 23
• AI Product Manager: 16
• Prompt Engineer: 12

Together they are still only about 1% of demand, so nobody should panic-rebrand their LinkedIn tonight. But THIS is growing and I won't be suprised to see these roles at the top in 2027 and 2028.

Forward Deployed Engineer is the one we would watch hardest. It came out of the AI labs and enterprise AI world, and it is the role for people who can build with AI and sit in front of a customer. That combo is rare and it will be a huge role in our opinion in the next decade.

Management is losing ground to IC (Individual Contributors)

• Individual contributor roles: ~83%
• Management track: ~11%
• Senior or strategic IC: ~6%

More than four out of five sessions are aimed at hands-on IC seats. When demand tilts that hard toward IC, it usually means companies are hiring people to do the work, not just to manage it.

So what should you actually do

Short version, by where you are starting from.

If you are a data analyst or data scientist, do not fight the shift, ride it. Move toward AI/ML Analyst and AI Engineer work. The skills transfer and the demand is moving your way.

If you are a software engineer, you are in the biggest and safest pool, and also the most crowded one. AI Engineer is where the same skill set earns a premium right now.

If you are early career, aim at the clusters with momentum, not only the famous logos. The AI labs and defense companies pull demand far above their size and draw a smaller crowd per opening.

Whatever you are, the center of gravity moved in 2026, and it moved toward AI.

Caveats from this analysis

• This is interview-prep behavior on one platform. It is an early demand signal, not a count of open roles or hires.
• We derived company and role from the guide pages people opened, using the roughly 58,000 sessions where both were cleanly attributable out of the 231,000+ total.
• Traffic grew across the year, so all trend numbers are reported as change in share of the mix, not raw growth, to avoid mistaking platform growth for market demand.
• Company-level quarter-to-quarter shifts are noisier than role-level ones, so company rankings use full-period totals.
• Everything is current through mid-June 2026.

If you want to see more insights like these, let us know in the comments! Would love to get your feedback as well, as this is #1 priority for us.

Thank you for reading!

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