applied ai · every layer of the stack
Whether it's the foundations of the data lake, the pipes that feed it, or the agents deployed across your procurement process. We place the people who build it.
deploy — invoice-agent
running
▸
the stack
We hire across all four, from the engineers holding it up to the executives who own it. Hiring from Senior to Chief · VP.
01
AI deployment
Ships it into production
02
AI platforms
Serves and runs the models
03
AI data
Feeds it and retrieves from it
04
AI infrastructure
The compute underneath
The gap we close
What the market sends
What we place
Coverage
Senior engineer → Chief AI Officer
Takes the model into the business. Owns what ships, the evals that gate it, and the fallback when it breaks. Sits with the CFO in the morning, ships production code in the afternoon.
TitlesAI Deployment Architect · Forward Deployed Engineer · Head of AI Delivery · Chief AI Officer
Senior engineer → VP AI Platform
Makes deployment repeatable. Serving, inference, orchestration, observability. The reason the second model ships faster than the first, and the reason the first one stays up.
TitlesML Platform Engineer · MLOps Lead · Head of ML Platform · VP AI Platform
Senior engineer → VP AI Data
Feeds the model and gets the answer back out. Pipelines, retrieval, context. Decides what the model actually sees, which decides whether anyone trusts it.
TitlesAI Data Engineer · Retrieval Engineer · Head of AI Data · VP Data
Senior engineer → VP AI Compute
The compute underneath. GPU clusters, scheduling, training fabric, capacity. Building the data centre is someone else's job. Making the GPUs useful is this one.
TitlesGPU Platform Engineer · Cluster Engineer · Head of AI Compute · VP Compute
Hundreds
AI roles closed
Engineer → C-suite
Every level we hire
London → Singapore
And everywhere in between
5 yrs
Building AI teams
If your AI is stuck in pilot, we should talk.