Opportunity Details

The client seeks a VP AI Engineer to design and deploy agentic AI systems that automate and optimize large-scale production environments. This role will support the development of LLM-powered solutions that can diagnose issues, reason over complex systems, and take secure, auditable actions, while also building retrieval-augmented generation (RAG) pipelines and domain knowledge systems with strong data quality, feedback loops, and governance.

You will productionize LLM capabilities by creating evaluation frameworks, prompt orchestration, response validation, and self-correction loops, and by integrating AI agents with observability, incident management, deployment, and runtime platforms. The position also emphasizes implementing safety, reliability, and compliance guardrails, including policy enforcement, rollback strategies, and circuit breakers, while optimizing performance, cost, and latency through techniques such as prompt engineering, caching, routing, batching, and streaming.

The ideal candidate will hold a bachelor’s degree in a quantitative or computational field, with a master’s or PhD preferred, and will have at least 7+ years of experience in applied machine learning, data science, or software engineering in production environments. Strong hands-on development skills in Python (or C++/Java/Go) are expected, along with practical expertise in LLMs, including prompt engineering, fine-tuning or adaptation, RAG, tool-calling agents, and vector search, plus demonstrated ability to build secure, explainable, reliable AI systems with governance and auditability.