Prompting fundamentals
LLM basics, token limits, temperature, top-p, stop sequences, system prompts, roles, instruction hierarchy, and prompt constraints.
Prompt engineer pre-employment test
Screen practical AI communication skills with a Prompt Engineer Pre-Employment Test.
Evaluate prompt design, LLM behaviour, context management, few-shot techniques, structured outputs, tool use, AI agents, testing, safety, and real-world prompt engineering before technical interviews.
Prompt design & structureContext engineeringTool use & AI agentsEvaluation, safety & optimisation
Skill signals
What this Prompt Engineer pre-employment test helps you evaluate
Measure practical prompt-engineering capability through role-relevant prompt tasks, LLM behaviour scenarios, tool-use workflows, evaluation exercises, and structured reports.
Prompt design
Zero-shot, one-shot, few-shot, chain-of-thought strategy, ReAct, self-consistency, output formatting, templates, and structured prompts.
Context engineering
Context-window management, memory, summarisation, retrieval context, prompt compression, information ordering, and context optimisation.
LLM behaviour
Hallucination, bias, robustness, instruction following, refusal behaviour, alignment, reasoning limits, and response control.
Tool use & AI agents
Function calling, APIs, tools, agent loops, planning, memory, orchestration, multi-step workflows, retries, and failure handling.
Evaluation & testing
Prompt benchmarks, human evaluation, A/B testing, regression testing, quality metrics, test cases, cost, latency, and optimisation.
Safety & guardrails
Prompt injection, jailbreak resistance, content filters, PII protection, permissions, policy enforcement, red teaming, and responsible AI.
Best practices
Prompt libraries, versioning, documentation, observability, reusable patterns, experiments, monitoring, collaboration, and continuous improvement.
Assessment flow
A practical structure for fair Prompt Engineer screening
Run a consistent, candidate-friendly process with secure delivery, practical prompt tasks, automated evaluation, and decision-ready skill reports.
01
Invite candidates
Send the Prompt Engineer test by email or share a secure assessment link with applicants.
02
Run practical prompt tasks
Candidates design prompts, control outputs, diagnose failures, use tools, test guardrails, and improve response quality.
03
Auto-evaluate
Score instruction quality, output accuracy, consistency, safety, creativity, format compliance, cost awareness, and best practices.
04
Review detailed reports
Compare prompt skill breakdowns, task-level analysis, evaluation results, scorecards, and hiring recommendations.
Score breakdown
Example Prompt Engineer score areas
Use cases
Where this pre-employment test fits best
Prompt Engineer hiring
Validate prompt design, context engineering, LLM behaviour, testing, tool use, safety, and optimisation skills before interviews.
AI product and automation teams
Assess candidates building copilots, assistants, chatbots, agents, content workflows, enterprise search, and intelligent automation.
Graduate and campus hiring
Identify candidates with strong AI fundamentals, communication, experimentation, analytical thinking, and prompt-design potential.
Use practical prompt tasks, automated evaluation, and explainable score reports to shortlist stronger Prompt Engineer candidates with confidence.
Identify Prompt Engineers who can create reliable, safe, and effective AI interactions.
Use structured tasks, automated evaluation, and clear reports to shortlist stronger engineering candidates faster.