AI-native roles
Hire LLMOps Engineers
Infrastructure engineers who keep dozens of models, thousands of requests per minute and a finite budget from colliding.
An LLMOps engineer runs language model infrastructure in production: gateway routing, caching, latency budgets, observability and cost enforcement. Hire one when model spend becomes a real line item or when reliability starts affecting customers. Expect $90 to $170 per hour by seniority and scale.
What this role actually does
LLMOps is what happens after the prototype works. You now have several models from several providers, each with different rate limits, failure modes, pricing and latency characteristics. Teams across the company are calling them directly. Nobody can answer which feature is responsible for last month's bill, and when a provider degrades, your product degrades with it.
An LLMOps engineer puts a gateway in front of all of that — commonly LiteLLM — and turns model access into managed infrastructure: one routing layer, provider failover, semantic and exact caching, per-team budgets, structured tracing of every call, and latency service levels that product teams can actually design against.
Core skills to look for
- Gateway and routing design, typically with LiteLLM across multiple providers
- Failover and fallback chains that degrade gracefully instead of erroring
- Caching strategy: exact-match, semantic and prompt-prefix caching
- Cost attribution and enforcement per team, feature and customer
- Latency engineering: streaming, speculative execution, concurrency control
- Observability: tracing, token accounting, error taxonomies, alerting
- Self-hosted inference where it pays: vLLM, batching, GPU scheduling
- Kubernetes, Terraform and the usual production platform foundations
When you need to hire this role
- Model spend has become a line item somebody senior asks about
- A provider outage takes your product down with it
- Latency is inconsistent and nobody can say why
- Multiple teams call models directly with no shared standards
- You want to move some traffic to self-hosted models but cannot quantify the trade-off
How to assess candidates for this role
Ask about a real incident
Have them walk through a provider degradation they handled. Look for concrete detection signals and a fallback that actually shipped, not a theoretical architecture.
Probe cost attribution
Ask how they would answer 'which feature caused this month's increase'. Strong answers describe request tagging and token accounting built in from the start.
Test caching judgement
Ask where semantic caching is dangerous. Good candidates immediately raise personalisation, freshness and correctness risks rather than treating caching as free.
Check the build-versus-buy reasoning
Ask when self-hosting beats an API. Expect a quantified answer involving sustained throughput, GPU utilisation and engineering cost — not ideology.
Typical rate bands
| Level | Experience | Typical rate | What they own |
|---|---|---|---|
| Mid-level | 4-6 years | $90-120/hr | Operates an existing gateway, owns dashboards and alerting |
| Senior | 7-10 years | $120-150/hr | Owns routing, caching and cost architecture across teams |
| Staff / Principal | 11+ years | $150-170/hr | Designs the model platform and the organisation's cost and reliability model |
Frequently asked questions
What is LLMOps?
LLMOps is the operational discipline of running language models in production: routing requests across providers, handling failover, caching, enforcing budgets, instrumenting traces and holding latency service levels. It is closer to platform engineering than to machine learning research.
When do we need a dedicated LLMOps engineer?
Usually when model spend becomes significant enough to be questioned, when a provider incident causes a customer-visible outage, or when several teams are calling models directly with no shared standards. Before that, an existing platform engineer can generally cover it.
Why route through LiteLLM instead of calling providers directly?
A gateway gives you one place to implement failover, caching, cost attribution, rate limiting and tracing. Calling providers directly from application code spreads that logic across every service and makes provider changes expensive.
How much does an LLMOps engineer cost?
Typical vetted contract rates run $90 to $120 per hour at mid-level, $120 to $150 at senior and $150 to $170 for staff and principal engineers, varying with traffic volume and whether self-hosted inference is in scope.
Can an LLMOps engineer reduce our model spend?
Usually yes, often substantially, through routing cheaper models to easier requests, caching, trimming context and reducing unnecessary reasoning steps. The size of the reduction depends entirely on how the system was built, so treat any fixed percentage promise with suspicion.