AI Engineer

Responsible for building, evaluating, deploying, and operating ML/LLM systems that deliver [Product/Service] capabilities for [Target Audience].

You are lead AI engineer on [Project Name] adding RAG to [Product/Service] for [Target Audience].
Leadership asks which model powers [Product/Service] AI features vs [Competitors].
Product debates **fine-tuning vs prompt engineering** for a [Industry]-specific assistant in [Project Name].
Production LLM traffic grew 5x for [Product/Service] customer assistant.
Legal flagged risks for a customer-facing chatbot in [Product/Service].
ML features for [Product/Service] suffer from training-serving skew.
GPU spend for training [Project Name] models exceeded forecast by 35%.
Product wants **agentic workflows** automating tasks for [Target Audience] admins in [Product/Service].
Ethics review requested bias testing for [Product/Service] ranking model affecting [Target Audience].
Training data for [Industry] models is insufficient; labeling is expensive.
Models ship manually today; [My Team Name] needs reliable ML delivery.
[Project Name] will add **multimodal** inputs (docs, images) for [Target Audience] workflows.
RAG latency spikes when scaling [Product/Service] knowledge base for [Industry] clients.
CFO asks whether to run inference **on-prem vs cloud** for [Product/Service] AI features.
EU customers require documentation under emerging **AI Act** rules for [Product/Service].
Write a RAG pipeline architecture review checklist for [Project Name] adding retrieval to [Product/Service] for [Target Audience].
Design an LLM evaluation framework for [Product/Service] release gates at [Company Name].
Architect agent orchestration for multi-step workflows on [Product/Service] at [Company Name].
Specify production observability for [Product/Service] AI features: distributed tracing, prompt/response logging, feedback loops, cost attribution by feature, drift detection, and alerting thresholds.
Write a cross-functional model selection memo for [Product/Service] at [Company Name] vs [Competitors].
Build a red-team prompt suite for [Product/Service] customer-facing agents at [Company Name].
Design structured output schemas for tool-calling agents on [Product/Service].
Create an inference cost optimization plan for [Product/Service] AI features at [Company Name].
Draft EU AI Act technical documentation template for high-risk [Product/Service] AI system at [Company Name].
Monthly ML ops review for [Project Name] at [Company Name]: eval regression results, production drift metrics, incident count, inference cost trends, model version status, red-team findings, and action items tied to [My Personal Goal] and [Key Metric].

AI Engineer

Responsible for building, evaluating, deploying, and operating ML/LLM systems that deliver [Product/Service] capabilities for [Target Audience].

You are lead AI engineer on [Project Name] adding RAG to [Product/Service] for [Target Audience].
Leadership asks which model powers [Product/Service] AI features vs [Competitors].
Product debates **fine-tuning vs prompt engineering** for a [Industry]-specific assistant in [Project Name].
Production LLM traffic grew 5x for [Product/Service] customer assistant.
Legal flagged risks for a customer-facing chatbot in [Product/Service].
ML features for [Product/Service] suffer from training-serving skew.
GPU spend for training [Project Name] models exceeded forecast by 35%.
Product wants **agentic workflows** automating tasks for [Target Audience] admins in [Product/Service].
Ethics review requested bias testing for [Product/Service] ranking model affecting [Target Audience].
Training data for [Industry] models is insufficient; labeling is expensive.
Models ship manually today; [My Team Name] needs reliable ML delivery.
[Project Name] will add **multimodal** inputs (docs, images) for [Target Audience] workflows.
RAG latency spikes when scaling [Product/Service] knowledge base for [Industry] clients.
CFO asks whether to run inference **on-prem vs cloud** for [Product/Service] AI features.
EU customers require documentation under emerging **AI Act** rules for [Product/Service].
Write a RAG pipeline architecture review checklist for [Project Name] adding retrieval to [Product/Service] for [Target Audience].
Design an LLM evaluation framework for [Product/Service] release gates at [Company Name].
Architect agent orchestration for multi-step workflows on [Product/Service] at [Company Name].
Specify production observability for [Product/Service] AI features: distributed tracing, prompt/response logging, feedback loops, cost attribution by feature, drift detection, and alerting thresholds.
Write a cross-functional model selection memo for [Product/Service] at [Company Name] vs [Competitors].
Build a red-team prompt suite for [Product/Service] customer-facing agents at [Company Name].
Design structured output schemas for tool-calling agents on [Product/Service].
Create an inference cost optimization plan for [Product/Service] AI features at [Company Name].
Draft EU AI Act technical documentation template for high-risk [Product/Service] AI system at [Company Name].
Monthly ML ops review for [Project Name] at [Company Name]: eval regression results, production drift metrics, incident count, inference cost trends, model version status, red-team findings, and action items tied to [My Personal Goal] and [Key Metric].