Primitives

fai-architect

Senior cloud-native solution architect — Azure Well-Architected Framework alignment, AI system design, multi-service integration, cost modeling, trade-off analysis, and production readiness assessment.

• reliability
• security
• cost-optimization
• performance-efficiency
• +2

fai-azure-ai-foundry-expert

Azure AI Foundry specialist — Hub/Project resource model, Model Catalog deployment, Prompt Flow orchestration, evaluation pipelines with groundedness and safety metrics, fine-tuning workflows, and model lifecycle management across dev/staging/prod environments.

• operational-excellence
• security
• cost-optimization
• responsible-ai

fai-azure-openai-expert

Azure OpenAI specialist — model deployment types (PTU/PAYG/Global), content filtering, structured output, token optimization, multi-region load balancing, and production inference patterns.

• cost-optimization
• performance-efficiency
• security
• responsible-ai

fai-fine-tuning-expert

Fine-tuning and MLOps specialist — LoRA/QLoRA techniques, JSONL training data preparation, Azure OpenAI fine-tuning workflow, hyperparameter tuning, evaluation-driven iteration, and model versioning.

• cost-optimization
• operational-excellence
• responsible-ai

fai-play-10-tuner

Content Moderation tuner — per-category severity calibration, blocklist optimization, false positive reduction, routing distribution, and moderation cost analysis.

• responsible-ai
• cost-optimization

fai-play-13-builder

Fine-Tuning Workflow builder — Azure OpenAI fine-tuning, JSONL data preparation, LoRA/QLoRA techniques, MLflow experiment tracking, evaluation-driven iteration, and A/B deployment.

• operational-excellence
• cost-optimization
• responsible-ai

fai-product-manager

AI product management specialist — requirements gathering, AI use case prioritization, evaluation metric design, go-to-market strategy, and responsible AI impact assessment.

• responsible-ai
• cost-optimization
• operational-excellence

fai-prompt-engineer

Prompt engineering specialist — system message design, few-shot patterns, chain-of-thought, structured output schemas, anti-hallucination techniques, and evaluation-driven prompt optimization.

• reliability
• responsible-ai
• cost-optimization

ai-prompt-safety-waf

AI prompt safety in application code — input sanitization, output validation, structured output enforcement, content filtering, token budget management, system message protection, and secure logging for LLM-integrated applications.

• responsible-ai
• security
• cost-optimization

azure-ai-document-intelligence-waf

Azure AI Document Intelligence standards — model selection, layout analysis, table/form extraction, custom models, batch processing, confidence thresholds, SDK usage, and Bicep deployment.

• reliability
• performance-efficiency
• cost-optimization
• security
• +1

azure-ai-language-waf

Azure AI Language standards — text analytics, NER, sentiment analysis, PII detection, summarization, CLU, custom text classification, healthcare NLP, SDK patterns, and batch processing.

• responsible-ai
• reliability
• performance-efficiency
• security
• +1

azure-ai-speech-waf

Azure AI Speech standards — STT (real-time + batch), TTS (neural voices, SSML, custom voice), speech translation, pronunciation assessment, speaker recognition, WebSocket streaming, SDK patterns, and latency optimization.

• performance-efficiency
• reliability
• security
• cost-optimization
• +1