Vikaas · Recruitment consultancy
Most companies trying to hire AI talent do not know what good looks like, so they over-pay for the wrong skills or pass on the right ones. This is advisory: we help you build the AI hiring function, not just fill one seat.
Role definition, level and comp benchmarking, sourcing strategy, and an interview process that can actually tell a builder from a buzzword — drawn from how Banao hires its own engineers.
Banao — hires AI and ML engineers for its own ~300-person company every week; this is that playbook.
Hiring AI talent well is a system, not a job post. We help you build the system and hand it to your team.
We translate a fuzzy 'we need AI people' into specific roles, levels, and the skills each one genuinely requires.
What AI and ML talent actually costs by level and market, so you neither over-pay nor lose offers you should win.
Where the people you need actually are and how to reach them — beyond posting a job and waiting for noise.
An evaluation that separates people who have shipped from people who can talk, modelled on Banao's own screen.
Metrics shown dotted (··) are being finalised in our case-study metrics pack. The practice is real; we will not publish a number before it is verified.
Banao (internal)
Banao hires AI and ML engineers for its own teams continuously and has tuned the role definitions, comp bands, and interview process against real outcomes. The consultancy hands you that playbook.
Studylab AI · Manentia AI
Banao has delivered engineering for AI-first companies like Studylab AI and Manentia AI — work that informs how we advise on hiring AI talent.
Banao hires AI and ML engineers for a ~300-person company every week. The role maps, comp bands, and interview rubrics we hand you are the ones we use ourselves and correct when they fail.
A recruitment consultant who has never had to ship on their own hires is guessing. We are not — we live with every hiring decision we recommend.
Sometimes advice is not what the situation calls for. We will say so:
We diagnose before we prescribe.
We audit your current AI hiring — roles, comp, sourcing, interview — and hand back a prioritised set of fixes. Yours to act on with us or alone.
Role maps, comp bands, sourcing plan, and an interview process designed with your team and tested on real candidates.
We can run sourcing for you through Vikaas, or hand the playbook to your team and step back. Your call.
Is this advisory, or do you also place candidates?
It starts as advisory — building your hiring function. From there you can run it yourself, or have Banao source candidates through Vikaas and screen them through InterviewGod. The consultancy and the placement work fit together but you can take either alone.
How is this different from RPO?
RPO runs your recruiting pipeline for you, ongoing. The consultancy builds the function — roles, comp, sourcing, interviews — and can then hand it to your team. Choose RPO to outsource the running; choose consultancy to own a working process yourself.
What makes your hiring advice credible?
Banao hires AI and ML engineers for its own 300-person company every week and has corrected its role definitions, comp bands, and interview process against real outcomes. We advise from a playbook we depend on, not from theory.
How long does it take to see value?
The one-week Hiring Discovery Sprint produces a prioritised set of fixes you can act on immediately. Building the full function out runs longer, but you leave the first week with something usable.
Bring the roles you keep mis-hiring or cannot fill. In 30 minutes we'll show where the process is leaking and how to fix it.
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