Hire Pre-Vetted LLMOps Engineers in Under 14 Days
Getting an LLM demo working is easy. Running it reliably and affordably in production is the hard part — and it’s exactly what LLMOps engineers do. Get a senior, AI-fluent LLMOps engineer from LATAM or APAC who overlaps your hours, at $35/hour.
✔ Sub-14-day placement ✔ US time-zone overlap ✔ Vetted on real work ✔ Cancel anytime, 2 weeks’ notice
Why LLMOps talent is almost impossible to hire in-house
LLMOps is one of the newest engineering disciplines on the planet, and the supply of people who have actually shipped and operated LLM systems at scale is tiny. Most teams discover the gap the hard way: a prototype works in a notebook, then falls over on cost, latency, or hallucinations the moment real users arrive.
Hiring for it domestically means competing for a handful of senior people commanding $200K+ packages, with months of search time you don’t have. Divogue gives you an engineer who has already done this work — evaluation pipelines, prompt versioning, RAG infrastructure, cost control — without the salary or the wait.
What our LLMOps engineers are vetted on
Every LLMOps engineer we place is screened on running real LLM systems in production, not on theory.
| Area | What we test for |
|---|---|
| Deployment | Model serving, inference scaling, latency and cost optimization |
| RAG and retrieval | Vector databases, embeddings, retrieval pipelines, chunking strategy |
| Evaluation | Eval frameworks, prompt versioning, regression testing, guardrails |
| Observability | Tracing, logging, token and cost monitoring, drift detection |
| AI tooling | Daily use of Cursor, Claude, Copilot to ship faster |
What teams hire our LLMOps engineers for
Production RAG systems
Building and operating retrieval pipelines that stay accurate and fast as your data and traffic grow.
LLM cost and latency control
Cutting inference spend and response times without sacrificing output quality — often the difference between a viable product and an abandoned one.
Evaluation and guardrails
Standing up eval pipelines so you can ship prompt and model changes with confidence instead of guesswork.
Provider-agnostic infrastructure
Architecting systems that switch between Claude, GPT, and open models without rewrites.
The same engineer, half the cost, a fraction of the wait
| In-House US Hire | Divogue LLMOps Engineer | |
|---|---|---|
| All-in annual cost | $185K–$250K | ~$67K ($35/hr) |
| Time to start | 2–4 months | Under 14 days |
| Recruiting fee | 20–25% of base | $0 |
| Time-zone overlap | Full | Full US hours |
Trusted by teams shipping in production
Divogue engineers are embedded with companies building real products today — including Riskcast, BGO Software, and everyone.ai — across construction technology, healthcare software, and ML infrastructure.
Frequently asked questions
What exactly does an LLMOps engineer do?
They take LLM applications from prototype to reliable production — deployment, evaluation, retrieval infrastructure, monitoring, and cost control. Think DevOps, but for AI systems.
How quickly can one start?
Most placements are live in under 14 days from your first call.
What tools do they work with?
LangChain, vector databases like Pinecone and pgvector, eval frameworks, plus cloud serving on AWS and Azure. They’re also provider-agnostic across Claude, GPT, and open models.
Do they overlap US working hours?
Yes. We source from LATAM and APAC specifically for engineers who work your business hours.
What if the engineer isn’t the right fit?
Cancel with two weeks’ notice, no penalty. We’ll help you find a better match if you’d like to continue.
Book a free intro call
Pick a time that works for you. We’ll walk through your stack, your needs, and show you matched engineers within days.
Ready to get your LLM systems production-ready?
Book a free 30-minute call. Tell us what you’re building and we’ll show you matched LLMOps engineers within days.