Prompt engineers who ship versioned libraries.
Specialists who design, test and version production prompt libraries — chain-of-thought, tool-use, JSON-mode, refusal handling and A/B testing for agentic and assistant experiences.
- 48 hrs — 3 vetted profiles delivered
- Prompt libraries
- Evals & A/B testing
- Cost & latency tuning
30 minutes, no slides. A senior delivery lead reviews your stack and gives you a concrete pilot outline.
- OpenAI
- Anthropic
- AWS Bedrock
- Azure OpenAI
- LangSmith
A working pilot in 90 days — not a 40-page slide deck.
Versioned prompts, tool schemas, refusal handling and JSON-mode outputs designed for reliability.
Golden datasets, LLM-as-judge rubrics, offline evals and live A/B tests to prove every change.
Model selection, caching, batching and prompt compression to hit production budgets.
“Our prompt engineer cut inference cost 40% and improved eval scores at the same time — inside one sprint.”
Questions buyers ask us first.
- Are prompt engineers really a role?
- Yes — in production AI systems, prompts are versioned artifacts with tests, owners and release gates. Specialists own them.
- Which models do they work with?
- OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex and open-weights via vLLM.
- Contract or contract-to-hire?
- Both, including embedded engineers inside your existing AI teams.
- How do you version and test prompts in production?
- Prompts are treated as code — versioned in git, evaluated against golden sets, canary-released and monitored with drift and regression alerts wired into CI/CD.
Ready to see it in your stack?
30 minutes with a delivery lead. Your architecture, your KPIs, a concrete pilot outline you can defend internally.
Book a 30-min working session →