AI & niche talent
Hire AI and niche technical talent
AI, GenAI, Forward Deployed, data and MLOps engineers, screened on what they have built. Start by working out which role you actually need.
What we mean by niche
Niche roles are the ones where job titles blur and a wrong brief wastes months: AI engineering, forward deployed engineering, and the data and platform work that keeps AI running in production.
We help you decide which of these roles you actually need before we search, because a wrong brief is the main reason AI hires fail.
Which role do you need?
Match the problem to the role. Each row links to the full page for that role.
| Role | What they do | Titles buyers search for | You need this when |
|---|---|---|---|
| AI, GenAI & ML Engineers | What they doML engineers train and evaluate models. GenAI and LLM engineers build applications on top of foundation models: prompting, retrieval, tool use and evaluation. | Titles buyers search forMachine Learning Engineer, GenAI Engineer, LLM Engineer, AI Engineer | You need this whenYou are building or improving a model or an LLM-based product. |
| Forward Deployed Engineers | What they doWork directly with customers or an internal business team to turn a messy problem into deployed software. The job mixes engineering, integration work and customer communication. | Titles buyers search forForward Deployed Engineer, Solutions Engineer, Customer Engineer, Deployment Strategist | You need this whenThe problem is unclear and the software has to land inside a customer's or business team's world. |
| Data, MLOps & LLMOps Engineers | What they doBuild the data pipelines that feed models, deploy and monitor models, and run LLM applications reliably: evaluation, versioning, cost and latency. | Titles buyers search forData Engineer, Analytics Engineer, MLOps Engineer, LLMOps Engineer | You need this whenData is unreliable, or models work in a notebook but not in production. |
How we screen niche roles
The same standard across all three roles: evidence, not keywords.
Shipped work, not coursework
We ask what reached production, who used it, and what broke.
Engineering fundamentals
Code quality, testing and deployment. A model that cannot be deployed is not a hire.
Evaluation discipline
How the candidate measures quality for models and LLM outputs, including test sets and failure analysis.
Interviews by people who have built it
AI-assisted screening for evidence of real project work, followed by technical interviews run by people who have built similar systems. We share the notes with you.
How we get you from role to hire
Four steps, one accountable team, and a guarantee after the offer.
Intake
We map the role, tech stack, seniority, budget and must-haves with your hiring manager.
AI screen, expert interview
AI screening filters the pool in seconds. Experienced recruiters and technical leads interview whoever passes.
Shortlist
3 to 5 interview-ready profiles, typically within 48 hours for core tech stacks.
Offer and guarantee
We coordinate interviews, offer and joining. Permanent hires carry a 90-day replacement guarantee.
Common questions
- What counts as niche technical talent?
- We use the term for roles where job titles blur and a wrong brief is costly: AI, GenAI and machine learning engineers; Forward Deployed Engineers; and data, MLOps and LLMOps engineers.
- What is the difference between an ML engineer and a GenAI engineer?
- ML engineers typically train, tune and evaluate models. GenAI engineers build products on top of existing foundation models using prompts, retrieval and tools. Many roles need some of both, and we help you scope it.
- Should we hire a data engineer or an ML engineer first?
- If your data is not reliable, start with a data engineer. If data is solid and you need a model in production, start with an ML engineer who has deployment experience. We help you decide in the first call.
- How fast can you send a shortlist?
- For core tech stacks, a first shortlist within 48 hours. Specialist profiles can take longer, and we tell you at the start.
- Do you hire for research roles?
- Our focus is applied engineering. For research-heavy positions we will tell you honestly whether we are the right partner.
- Can these engineers work from India for US clients?
- Yes. Through our Onsite, Nearshore and Offshore models, engineers can work with overlap hours that suit your team, or be hosted inside a Build-Operate-Transfer centre in India.
Not sure which role you need?
Tell us the problem and the stack. We will help you scope the role, then confirm the timeline at the start.