Dedicated prompt engineering talent
Hire prompt engineers and prompt engineering experts from Relevance Lab — for prompt and context design, evaluation harnesses, guardrails and jailbreak testing, and token and cost optimisation.
Quick answerPrompt engineers from Relevance Lab design and test the prompts, context assembly and output schemas that make an LLM feature reliable — building evaluation sets, tuning for accuracy and format, hardening against jailbreaks and prompt injection, and cutting token cost and latency without losing quality. They pair with your developers on the prompt, retrieval and evaluation layer.
What prompt engineers you hire do
Prompt & context design
System prompts, few-shot examples, context assembly and structured-output schemas.
Evaluation harnesses
Curated, versioned test sets with automatic and LLM-as-judge scoring, and regression runs.
Guardrails & red-teaming
Prompt-injection and jailbreak testing, refusal behaviour, and content-policy enforcement.
Cost & latency
Trimming context, summarising history, right-sizing retrieved context — token count drives cost.
When to bring in a prompt engineer
| Situation | What they do | Outcome |
|---|---|---|
| Feature shipped, quality inconsistent | Add an eval harness, find failure modes | Measurable accuracy and format gains |
| Costs rising with usage | Context and caching optimisation | Lower cost per request, same quality |
| Security review flagged prompt injection | Harden prompts and add defences | Passes red-team testing |
Prompt talent that measures its work
Evaluation-first
They build a harness before they tune — improvements are measured, not asserted.
Security-minded
Injection and jailbreak defence is part of the job, not an afterthought.
Pair with your devs
Embedded in your team on the prompt, retrieval and evaluation layer.
Platforms behind them
RLCatalyst and Spectra, plus a bench for spikes.
Vetted for depth
Real prompt and evaluation engineering, not casual prompting.
You own it
Prompts, evaluations and configuration, in your repositories.
- AWS
- DataStax
- Salesforce
- Snowflake
Need engineers, not just prompts?
Hire LLM Developers or Generative AI Developers for the full application layer, or engage Generative AI Development Services for a fixed-scope build.
Making LLM features reliable
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Content last reviewed: September 2026
Scaling this across the enterprise?
Our Enterprise AI Services practice brings generative AI, agents and LLMs to production at scale — with the governance, platform and operating model to keep them reliable, compliant and cost-controlled.
Need a prompt engineer on your team?
Share the use case and stack and we will send named candidate profiles within days.
Hire Prompt Engineers
Share the role, your stack and your timeline. We send named candidate profiles within days, and engineers typically start within 1–3 weeks — staff augmentation, team extension or a managed AI pod.