Principal Data Scientist, Agentic AI Technical Lead

Role overview A senior leadership seat for a deeply experienced data scientist and AI engineer to act as technical lead across an entire agentic AI program. The role spans architecture, evaluation, delivery management, and executive advisory across multiple workstreams inside a large delivery organization. It is built for someone who sets direction, raises quality, and owns the call when the stakes are high.

Responsibilities - Provide senior technical oversight across every agentic AI workstream, from problem framing through evaluation, deployment, and ongoing operation - Define technical strategy and reference architecture for agentic systems, including multi-agent orchestration, tool and function calling, RAG, vector databases, embeddings, and streaming responses - Manage cross-team dependencies, resolve blockers, and keep velocity and quality high as the program scales - Set standards for model development, experimentation, and the path from research to production - Establish evaluation frameworks covering quality, safety, hallucination, cost, and latency for LLM and agent systems - Mentor technical leads, champion engineering standards, and own high-stakes decisions across the program

Requirements - 12+ years of experience in data science and AI/ML with a record of taking AI systems from research to production - Strong executive presence and the ability to communicate credibly with senior stakeholders and client leadership - Hands-on experience with LLMs and agentic systems, including prompt engineering, function and tool calling, multi-agent orchestration, RAG architectures, vector databases, embeddings, and streaming LLM responses - Deep expertise in model evaluation, experimentation design, and applied statistics, including evaluation approaches specific to generative and agentic systems - Strong Python skills and fluency with the modern data science and ML stack - Background in MLOps and AI infrastructure, including model versioning, monitoring, deployment automation, and reproducibility

Nice to have - Experience supporting AI programs in regulated industries such as life sciences, healthcare, or financial services - Consulting or client-facing technical leadership experience - Background in fine-tuning, evaluation automation, or agent safety and guardrails