Hire Generative AI Developers — From Pilot to Production
Stuck in GenAI pilot purgatory? CompanyBench matches you with pre-vetted developers who fine-tune, deploy, and productionize LLM applications — not just call an API. Available on contract, contract-to-hire, or full-time.
Why Hire a Generative AI Developer
Your team can call an LLM API. That's not the hard part anymore. The hard part is getting a GenAI feature past the demo — handling hallucinations, controlling inference cost at scale, fine-tuning on your own data, and integrating it safely into a product people actually use.
Most in-house teams have the first skill and not the second. A generative AI developer closes that gap — turning a working prototype into a reliable, production-grade system.
GenAI Developers by Sub-Specialty
Tell us which sub-specialty your project needs — we match accordingly from our pre-vetted pool.
LLM Integration
Wiring frontier and open-source models into your product via API or self-hosted inference.
Core Stack
Fine-Tuning
Adapting models to your own data with LoRA, QLoRA, SFT, and RLHF/DPO.
Core Stack
RAG & Deployment
Retrieval-augmented pipelines, vector databases, and production-grade model serving.
Core Stack
Skills & Tech Stack We Cover
Our GenAI developers have deep expertise across the full breadth of LLM tooling.
LLM Integration
Frameworks
Fine-Tuning
RAG & Retrieval
Deployment & Ops
How It Works
From requirements to a shipping developer, in days.
Share Requirements
Tell us your use case, target models, and project scope.
Get Matched
Receive 2-3 pre-vetted GenAI developer profiles within days.
Interview & Select
Evaluate expertise and fit with your shortlisted candidates.
Onboard & Ship
Most hires are productive and shipping within a week.
Industries We've Staffed For
Compliant chatbots, RAG-based search, and AI-driven content and automation across regulated and high-growth industries.
Frequently Asked Questions
Everything you need to know about hiring generative AI developers through CompanyBench.
They integrate and fine-tune large language models, build RAG pipelines, and deploy GenAI features into production systems — going beyond simply calling an API.
The terms overlap. An LLM engineer typically focuses more deeply on model fine-tuning and evaluation, while a generative AI developer covers broader application integration.
Yes. Our vetting process screens for real fine-tuning experience, such as LoRA and QLoRA, not just prompt engineering on frontier APIs.
Rates are significantly below US/EU market rates for equivalent experience. Contact us for a role-specific quote based on scope and seniority.
Contract, contract-to-hire, and full-time — suited to bounded pilots as well as long-term AI product roadmaps.
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