Hire an AI Engineer
The engineer who turns LLM capability into product reality.
'AI Engineer' is the most crowded, noisiest title in tech
- Retained recruiters.
- LinkedIn Recruiter seats.
- Keyword-matched resumes.
- Templated InMails.
Every engineer updated their LinkedIn with 'AI' in 2024. Your sourcing inbox is now full of people who've called an OpenAI endpoint once and now describe themselves as AI engineers.
The candidates who can actually build with LLMs (who understand retrieval, evals, tool use, caching, and how to ship against a moving model floor) are a small slice of that pool. They're often shipping real AI products and have no need to job-hunt.
You need sourcing that can distinguish 'has a repo with an OpenAI SDK call' from 'has shipped an evaluated, production-grade AI product.'
How Superposition finds your AI engineer
Real shipping signal
Our agent evaluates production AI work: eval harnesses, agent frameworks, RAG systems, and blog posts that show actual depth.
Frontier-fluent intake
Our voice agent speaks the language (MCP, tool use, prompt caching, LLM-as-judge) so the requirements get captured precisely.
Cuts the LinkedIn noise
No candidates with 'AI' tacked onto a resume. Only engineers with demonstrable, shipped AI work.
Speed in a hot market
AI engineers get snapped up fast. We surface curated shortlists in weeks, not months.
Questions.
Answered.
An AI engineer builds product on top of foundation models: retrieval, evaluation, latency, cost, the prompt and tool layer. An ML engineer owns models and training. Different jobs, often confused.
The title is new, the skills are not. The strongest candidates are usually product engineers who have shipped something with a model in the loop and written about what broke.
Evaluation. Anyone can wire up a model; the people worth hiring can tell you how they knew whether output got better or worse, which the agent asks in the first exchange.
Usually not. For most AI products the hard parts are retrieval quality, evaluation and cost, none of which require training experience.
Hire a Data Engineer
The engineer who owns the pipes your analytics and ML run on.
Hire a Product Designer
The designer whose work defines how your product feels.
Superposition vs. hireEZ
hireEZ expands the search surface. Superposition turns the search surface into qualified conversations.
Find your AI engineer.
Get builders who ship evaluated LLM products, not resume keyword-stuffers.