PromptEval careers
Most prompt engineering tools solve one problem: they log your prompts,
or they test them, or they store them. PromptEval is the first tool that
covers the full lifecycle — from evaluation to deployment.
The core is a prompt quality scorer that gives any prompt a score from
0 to 100 across four dimensions: clarity, specificity, structure, and
robustness. Unlike generic LLM wrappers like PromptLayer or LangSmith,
PromptEval doesn't just track what you sent — it tells you what's wrong
and why, with a full technical breakdown and concrete recommendations.
From there, the ecosystem extends in every direction:
→ Prompt Library with full version history — iterate without losing
what worked before
→ Production Iterator — surgical, targeted improvements to existing
prompts without rewriting from scratch
→ Playground — test your prompt against any scenario in real time
before it ever touches production (Pro)
→ AI-powered rewrite — get an improved version of your prompt instantly
(Pro)
→ Prompt Map — a visual conflict graph that flags when instructions in
your prompt contradict each other, color-coded by severity
→ REST Evaluation API — integrate prompt quality scoring directly into
your CI/CD pipeline (Team)
→ Library Slug API — serve versioned prompts directly from PromptEval
to your production app, no redeploy needed when a prompt changes (Team)
The result: teams stop guessing why their LLM outputs are inconsistent
and start treating prompts as a first-class engineering artifact —
versioned, scored, and deployed with the same rigor as code.
or they test them, or they store them. PromptEval is the first tool that
covers the full lifecycle — from evaluation to deployment.
The core is a prompt quality scorer that gives any prompt a score from
0 to 100 across four dimensions: clarity, specificity, structure, and
robustness. Unlike generic LLM wrappers like PromptLayer or LangSmith,
PromptEval doesn't just track what you sent — it tells you what's wrong
and why, with a full technical breakdown and concrete recommendations.
From there, the ecosystem extends in every direction:
→ Prompt Library with full version history — iterate without losing
what worked before
→ Production Iterator — surgical, targeted improvements to existing
prompts without rewriting from scratch
→ Playground — test your prompt against any scenario in real time
before it ever touches production (Pro)
→ AI-powered rewrite — get an improved version of your prompt instantly
(Pro)
→ Prompt Map — a visual conflict graph that flags when instructions in
your prompt contradict each other, color-coded by severity
→ REST Evaluation API — integrate prompt quality scoring directly into
your CI/CD pipeline (Team)
→ Library Slug API — serve versioned prompts directly from PromptEval
to your production app, no redeploy needed when a prompt changes (Team)
The result: teams stop guessing why their LLM outputs are inconsistent
and start treating prompts as a first-class engineering artifact —
versioned, scored, and deployed with the same rigor as code.
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Francisco Gabriel de Souza Ferreira
Betterworks • Menlo Park • 1 week ago
Vyond • California • $265k – $315k • 2 weeks ago
Movable Ink • New York City • $123k – $160k • 2 weeks ago
Rockbot • Remote • $60k – $75k • 2 weeks ago
Brightidea, Inc. • San Francisco • $150k – $300k • 3 weeks ago






