Prompt Engineer / GenAI
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- Explain model behavior and design clear prompt contracts
- Ground prompts and control tools/agents
- Prove evaluation, safety and production discipline
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Prompt Engineer / GenAI Engineer / Conversation Designer
Benchmark: Current Prompt Engineer work: system instructions, templates, RAG, structured outputs, evaluation/versioning and adversarial testing 2026 interview refresh: Interview readiness now requires treating prompts as production assets with measurable quality, security and cost.
Enrichment
Explain model behavior and design clear prompt contracts
Prompt architecture + structured outputs
Practice: roles, constraints, examples and output schemas
Prompt critique + context design
Practice: failure diagnosis, context windows and instruction hierarchy
Ground prompts and control tools/agents
RAG-aware prompt design
Practice: citations, missing context, retrieval errors and synthesis
Tool / agent instructions
Practice: permissions, tool calls, MCP and escalation
Prove evaluation, safety and production discipline
Prompt evals + versioning
Practice: test sets, A/B, regressions, quality/cost metrics
Prompt security + red teaming
Practice: injection, jailbreak, data leakage and unsafe actions
Interview-Readiness Proof / Practice Loop
Run a live prompt-design case: turn an ambiguous business task into system/developer/user instructions, structured output, RAG context and one tool. Then create an eval set, compare two prompt versions, analyze failures and red-team the final design.
Pass Rubric
- Clear prompt contract
- correct context use
- robust structured output
- groundedness
- reproducible evaluation
- measurable task success
- version control
- prompt security
- latency/token-cost awareness
- ability to explain model limits