ARMMAN, Technical AI Analyst

The AI & Data Integrity Fellowship is a high-impact, technical role designed for someone who sits at the intersection of Generative AI and Data Engineering. While many focus solely on "chatting" with AI, this role is about industrializing those interactions. The Fellow will be responsible for ensuring that our LLM outputs are safe, accurate, and optimized for cost/latency, while simultaneously building the "trust layer" in our MySQL databases to ensure the AI isn't learning from—or reporting—garbage data.

Key responsibilities

LLM Optimization & Safety 

• Prompt Engineering & Testing: Design, version control, and A/B test system prompts to improve response accuracy and tone.
• Hallucination Mitigation: Implement "Chain of Thought" or "Self-Consistency" prompting techniques to reduce factual errors.
• Guardrail Development: Stress-test the model against prompt injections, PII leaks, and toxic outputs.
• Benchmarking: Create "Golden Datasets" to quantitatively score LLM performance (e.g., scoring responses on a scale of 1-5 for accuracy).

Data Quality & MySQL Engineering 

• Validation Layer: Build SQL scripts or Python triggers to ensure data entering the system meets specific formats and business logic.
• Quality Check Layer: Develop automated checks for null values, duplicates, and referential integrity within MySQL.
• RAG Readiness: Ensure that the data being retrieved for the LLM is "clean" and indexed properly for high-speed retrieval.