Hire AI Developers Who Take PoCs To Production
Your demo looks great in a notebook. Stakeholders are excited. Then the PoC stalls — no evals, no cost controls, no owner who can ship a safe RAG or agent path to real users.
We fix that bottleneck in 24 hours. Get matched with pre-vetted AI developers who work your hours, in your stack, and open their first pull request inside 72 hours.
No upfront feesYou interview firstFree replacementNDA before discovery
How it works
How To Hire An AI Developer In Four Steps
No job ad. No five-month search. No recruiter who confuses a notebook demo with a production RAG system. From first message to first pull request in under a week, and nothing to sign until you have met the engineer.
Share your requirements
Ten minutes on the form or a quick call: your product, your model stack, and whether you need RAG, agents, ML pipelines, or a PoC rescue.
No commitmentScope it with a senior lead
A 30-minute working session pins down skills, seniority, timeline, and a monthly budget you can take to finance.
Plan is yours to keepMeet 2–3 matched AI developers in 24 hours
Hand-picked from our vetted pool for your exact use case. You run the interviews and you pick the engineer.
You interview, you decideThey start shipping
We handle contracts, payroll, NDAs, and onboarding while your AI developer gets into the codebase.
First pull request under 72 hoursNot sure whether you need an LLM engineer, an ML specialist, or general production AI capacity? Most teams do not. That is what the scoping call is for.
Scope my AI hireOur edge
We Deliver Faster Because Our Own Process Runs On AI
Most agencies sell you hours. We engineered an in-house, AI-powered execution process that removes the slow parts of AI delivery, so the hours you pay for turn into production systems — evals, guardrails, and shippable PRs.
Cost comparison
How Much Does It Cost To Hire An AI Developer?
Finance wants one number. For AI roles, base salary is only part of the story. Here is the full cost side by side.
Figures are indicative monthly averages for a mid-level AI engineer. Your exact rate depends on seniority, specialization, and time-zone overlap, and typically lands between $35 and $130 per hour. Senior LLM, agent, and MLOps specialists sit at the top of that range.
Get a rate for your roleWhen to hire
Signs You Need To Hire An AI Developer
Most teams wait until the PoC is already stale. Tick the signals that sound like your team and see where you land.
Your self-check
0 of 6 signals ticked
Tick the signals on the right that match your team right now.
Why Techorizone
Why Engineering Leaders Pick Our AI Developers
Four things that decide whether an AI hire reaches production or stalls as another PoC.
01 Production-first, not PoC-first
Evals, observability, and guardrails ship with the feature. That is the difference between a demo your board liked and a system your customers can trust.
02 Top 3%, re-tested every year
Vetting is not a one-time gate. Engineers re-qualify as model APIs and agent patterns move, so a 2023 prompt trick does not get you a 2026 hire.
03 AI-native by habit
Claude, Copilot, and Cursor in daily use. Boilerplate is automated so senior hours go into retrieval quality, agent design, and cost control.
04 Wrong fit? Replaced free.
If the match is not working, we swap in a new AI developer within days at no cost. The risk of a mis-hire sits with us.
Technical depth
What Our AI Developers Build: RAG, Agents, And Evals
Eight areas every AI engineer we place is tested on before they meet you — from retrieval quality through to guardrails and production ownership.
Production RAG systems
Chunking, hybrid retrieval, reranking, citations, and eval suites that survive real documents — not a single happy-path demo.
AI agents & tool use
Multi-step workflows with tool calling, approvals, retries, and observability so agents fail safely under live traffic.
Evaluation harnesses
Regression tests for answer quality, latency, and cost before each release — so model upgrades do not silently break you.
Guardrails & safety
Prompt-injection defenses, PII handling, grounded answers, and human-in-the-loop where risk is high.
Inference cost control
Model routing, caching, prompt budgets, and token accounting so usage does not erase product margins.
LLM app engineering
Python/FastAPI services, streaming, session handling, and clean provider abstraction across OpenAI, Anthropic, and Bedrock.
ML pipeline ownership
Training-to-serving paths, monitoring, and drift checks when classical ML still belongs in the roadmap.
PoC rescue & hardening
Take a stalled notebook or vendor demo and harden it into something you can put in front of users.
Need more than one of these? Most teams hire one AI developer first, then add an LLM or ML specialist from the cluster.
Build my AI teamCompare your options
Techorizone vs Freelance Marketplaces vs Staffing Agencies
You are probably comparing us against a freelance marketplace and a recruiter in another tab. Here is that comparison on the things that decide whether your AI hire actually ships to production.
| Criteria | RecommendedTechorizone | Freelance marketplaces | Traditional staffing agencies |
|---|---|---|---|
| Time to first candidate | 24 hours | 3 to 7 days of sifting | 3 to 6 weeks |
| How AI skill is verified | Tested on production RAG, agents, and eval scenarios | Self-reported portfolios and ratings | Resume screen plus a generalist interview |
| Who picks the match | A senior engineer reads your AI use case | A keyword search you run yourself | A recruiter without AI production background |
| Engagement type | Full time, dedicated, embedded | Hourly, often split across clients | Permanent hire or temp placement |
| Upfront fees | None | None, but platform fees apply | 15% to 30% placement fee |
| If the fit is wrong | Replaced free, within days | You restart the search yourself | Extra fees usually apply |
| Payroll and compliance | Handled end to end by us | Your finance team handles it | Yours once the placement closes |
| Delivery oversight | Engagement manager included | None | None after placement |
| Scaling the team | Add or reduce monthly | Source from scratch every time | Slow hiring cycles |
| Cost against a US hire | Up to 49% lower, all in | Variable hourly, hard to forecast | Full salary plus agency fee |
Swipe to compare
Know who you are hiring
What Does An AI Developer Do?
An AI developer builds and maintains production AI systems your users touch — RAG pipelines, agents, LLM features, eval harnesses, and the guardrails that keep outputs safe and affordable.
Most of the week is engineering: Python services, retrieval quality, code review, CI with eval gates, and collaboration with product and data. A notebook demo is the starting point, not the finish line.
AI developer vs machine learning engineer
An ML engineer often owns training, classical models, and MLOps depth. An AI developer (as hired here) owns applied LLM/GenAI product work — retrieval, agents, evals, and shipping. Many roadmaps need both; the scoping call clarifies the mix, and our ML / LLM child pages go deeper.
Tech stack
The AI Stack Our Developers Already Know
No ramp-up tax on the basics. Tell us your model providers, retrieval stack, and runtime on the scoping call. We match engineers who have already shipped production AI on it.
LLM & orchestration
Retrieval & data
ML & frameworks
Quality & ops
Serving & product
Need a deep ML training lead, an LLM specialist, or a TensorFlow/PyTorch expert? Say so on the call. This hub covers production AI capacity; specialty pages go deeper — and we will tell you honestly if we cannot match.
Specializations
Hire AI Developers By Specialty
Use cases
What Companies Build With AI Developers
The same skills you are hiring for already run these products. Pick the path closest to your roadmap — specialist pages go deeper without diluting this hub.
LLM applications
Product copilots, support assistants, and grounded chat over your data — with evals and cost controls from day one.
Generative AI features
Content, summarization, and multimodal workflows wired into your product — not a disconnected sandbox.
Machine learning systems
Ranking, forecasting, and classical ML pipelines with monitoring when LLM wrappers are the wrong tool.
Framework specialists
TensorFlow or PyTorch depth when training and custom models are the bottleneck — routed to the right child page.
Global reach
Hire AI Developers With Global Overlap
Staff augmentation with the right balance of cost, production AI skill, and daily overlap with your team — not an overnight handover on a fragile model.
A global AI talent pool
Over 1000 vetted engineers across multiple regions, so your match is not limited to whoever happens to be free in one city this month.
Up to 49% lower cost
Global sourcing removes the US AI salary premium without dropping you to a shared agency pod or a part-time freelancer.
AI profiles in 24 hours
A pool this size is why 2–3 matched developer profiles reach you within a day instead of a quarter.
One dedicated AI owner
You get one full-time AI engineer focused on your production path, not a bench rotating across five demos.
Your stack, already known
Engineers fluent in Python, RAG stacks, agent frameworks, and the model providers you already run.
Built around your hours
Your developer is scheduled to your standups, eval reviews, sprint cadence, and release windows, not the other way round.
Working in a market that is not pinned? Tell us your hours and we will match a an AI developer around them.
Why it needs an owner
Why Production AI Needs A Dedicated Owner
AI features do not always fail loudly. They drift — a worse answer here, a silent tool failure there, a cost spike nobody budgeted. By the time someone notices, users already felt it.
Eval debt and unowned PoCs are why production AI needs a dedicated developer rather than borrowed hours from whoever is free between sprints.
- Evals gated in CI before model or prompt changes ship
- Retrieval and agent behavior traced under real traffic
- Guardrails and cost budgets treated as release criteria
- Runbooks your own team can operate without reverse-engineering notebooks
Locations
Hire AI Developers In Your Market
“Will my AI developer actually be online when my team is?” is the question we get most. Pick where you operate — each market covers typical overlap hours, contract currency, and how we align to your working day.
Hiring in a specific city?
Somewhere else on the list? See offshore hiring options or ask us directly.
Answers
AI Developer Hiring Questions, Answered
What does an AI developer do?
An AI developer designs, builds, and maintains production AI systems — RAG pipelines, agents, LLM product features, evaluation harnesses, and guardrails. Day to day that means writing and reviewing code, measuring quality and cost, and shipping to real users — not stopping at a notebook demo.
What is the difference between an AI developer and a machine learning engineer?
They overlap, but the focus differs. An ML engineer often owns training, classical models, and MLOps depth. An AI developer on this page owns applied LLM and GenAI product work — retrieval, agents, evals, and shipping. On a scoping call we look at your roadmap and recommend the right mix, including our ML or LLM specialist pages when needed.
How long does it take to hire an AI developer?
With Techorizone you review 2–3 matched candidates within 24 hours of your scoping call, and most engineers open their first pull request inside 72 hours of signing. Hiring the same role in-house typically takes six to ten weeks from job ad to first commit.
How much does it cost to hire an AI developer?
Techorizone AI developers start from about $5,600 per month for a full-time dedicated engineer, which works out to roughly $35 to $130 per hour depending on seniority and specialization. An equivalent US in-house hire averages about $11,000 per month in base salary before benefits, payroll tax, recruiting fees, and equipment, so the all-in saving is up to 49%.
Will they work in my time zone?
Yes. We match for overlap first, so your engineer joins your standups, Slack, and eval reviews live. US and Canadian engagements get four to six hours of daily overlap. UK, EU, and Middle East engagements get a near full working day.
Can an AI developer take our PoC to production?
Often that is exactly the assignment. Our engineers audit the demo for retrieval quality, eval coverage, guardrails, latency, and cost, then harden the highest-impact path instead of rewriting everything from scratch.
How does your AI-powered process help AI delivery?
Our in-house execution process uses AI tooling to remove repetitive work — boilerplate services, test scaffolding, and docs — so the hours you pay for go into architecture, evals, and production readiness. Teams typically ship up to 40% faster without cutting review standards.
What happens if the AI developer is not the right fit?
Tell your engagement manager and we replace the engineer within days at no cost. No debate and no exit fees. The risk of a mis-hire stays with us, not with you.
Zero risk
Hire AI Developers With Zero Risk
The reason most teams delay an AI hire is not the budget. It is the fear of getting another demo that never reaches users. We took that risk off your side of the table.
No upfront fees
We source, vet, and present AI developers before you pay anything. No retainer, no placement fee.
You interview first
Meet two to three matched engineers and approve the one you want. You decide, always.
Free replacement
If the match is not working, we swap in a new AI developer within days at no extra cost.
Payroll and compliance
Contracts, international payroll, NDAs, and IP assignment are handled on our side.
Response within 1 business day · NDA on request · No commitment
Get started
Your AI Developer Is
One Call Away
Thirty minutes with a senior engineering lead. You leave with a scoped plan and 2–3 candidates on the way, whether or not you hire us.
- Scope the highest-return PoC→production work in your roadmap
- Get a realistic timeline and a monthly cost you can take to finance
- Meet vetted AI developers within 24 hours
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