Senior AI engineers, without the six-month hiring cycle.
The AI talent market is brutal. Embedded engineers from Hypership give you senior AI capability in weeks, not quarters.
Why hiring AI engineers is so hard right now.
The demand for AI engineering talent has outstripped supply by an order of magnitude. Every company wants to hire AI engineers. Almost none of them can.
Senior engineers with genuine production AI experience — not just fine-tuning tutorials and demo apps — are among the most sought-after people in tech. They have multiple offers. They command top-of-market compensation. And they are usually not looking.
For startups and scaleups, the maths is brutal. A six-month hiring cycle, a senior salary plus equity, and the risk that you hire the wrong person. Meanwhile, your competitors are shipping.
The alternative — traditional outsourcing — usually means junior developers following a spec they do not fully understand, building AI features they have never built before. The output looks like it works in a demo. It breaks in production.
Embedded engineers, not outsourced contractors.
Hypership provides senior AI engineers who embed directly with your team. We call it the forward deployed engineer model. It gives you the capability of a senior hire without the hiring cycle, the overhead, or the risk.
Our engineers join your Slack, attend your standups, understand your domain, and ship production code. They are not writing to a spec in isolation. They are part of your team for the duration of the engagement.
The model works because we are AI-native. Our engineers build AI systems every day — agent teams, agentic workflows, LLM-powered applications, and AI-augmented development pipelines. They bring patterns and experience that a generalist full-stack developer simply does not have.
When the engagement ends, you keep everything. The code, the architecture, the documentation, and the knowledge transfer. No lock-in. No dependency. A clean handoff.
Everything a hire would give you. Faster.
The capability of a senior AI engineering team, available in weeks instead of months.
Senior AI engineers
Engineers with production experience in LLMs, agent systems, RAG, tool use, and AI infrastructure. Not generalists learning on the job.
Embedded delivery
Your Slack, your standups, your codebase. Engineers who understand your domain and work as part of your team, not a separate silo.
AI-native tooling
We bring our own AI-augmented development stack. Code review agents, automated testing, AI-assisted architecture. Your project benefits from how we work.
Clean handoff
Everything we build is yours. Production code, architecture decisions documented, knowledge transferred. No lock-in, no recurring dependency.
Is this you?
Startups that need to ship AI features now
You have raised funding and need to move fast. You cannot wait six months to build an AI team from scratch.
Scaleups adding AI to existing products
Your product works. You need AI capabilities integrated properly, not bolted on by someone unfamiliar with your stack.
Teams that have tried and failed to hire
You have been searching for months. The candidates are either too expensive, too junior, or not available.
Companies that need a fractional AI team
You do not need five full-time AI engineers. You need senior capability for a defined scope, then a clean handoff.
Transparent, not templated.
We do not publish a rate card because every engagement is different. But we believe in pricing transparency, so here is how it works.
Engagements are scoped after a discovery conversation. We will tell you what it costs before you commit. No surprises.
We work on both fixed-price and time-and-materials models. Fixed price works well for defined deliverables. Time and materials works well for ongoing embedded work where the scope evolves.
Most engagements run 4–12 weeks. Some extend into longer partnerships. We structure everything so you can stop at natural breakpoints without penalty.
Compared to a senior AI engineering hire (salary, equity, benefits, ramp time, management overhead), an embedded engagement typically costs less for the first 6–12 months and delivers faster because there is no hiring or onboarding lag.
Common questions.
Stop searching. Start shipping. Senior AI engineers embedded with your team in weeks.
One conversation. We will tell you honestly whether we are the right fit and what it would cost.