• Manage the feature backlog and delivery for synthetic and curated data streams used to train and fine-tune large-scale AI systems • Coordinate the end-to-end lifecycle of data pipelines, including synthetic data generation, human-in-the-loop (HITL) annotation, and reinforcement learning (RL) loops • Implement data quality checks, including coverage analysis, bias detection, and ethical filtering to ensure high-standard model inputs • Act as the bridge between AI researchers and engineers to identify data gaps and deliver the vital datasets or tools to keep development moving • Define clear product requirements for internal tools used for data collection, labeling, and augmentation at scale • Assist in crafting workflows for enterprise customers or academic partners to enable domain-specific LLM fine-tuning • Ensure data collection and usage align with established legal, privacy, and AI ethics guidelines