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Metro manager role with common engineering title and moderate brand, offset by niche agentic AI specialization.
Specialized agentic AI platform requirements moderately limit transferability despite general managerial and cloud skills.
Requires managerial experience plus specific LLMOps, cloud, observability, identity and governance expertise.
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Lead and grow a high-performing team of AgentOps Forward Deployed Engineers with end-to-end ownership of hiring, coaching, and career progression.
Own design, development, and operation of Pearson's internal agentic AI platform, ensuring reliability, observability, governance, and production readiness.
Translate agentic AI platform strategy into practical business outcomes by taking use cases from prototype to production and establishing standards for agent orchestration and LLMOps.
Experience leading, coaching, or mentoring engineers with responsibility for hiring, performance, and team growth.
Hands-on experience building LLM-powered systems, AI agents, or workflow automation in production, with strong Python and backend/platform engineering skills in cloud-native, distributed systems.
Experience with agent orchestration or multi-agent frameworks (e.g. CrewAI, LangGraph, ADK) and LLM observability tooling.
Bachelor's or Master's degree in Computer Science, AI/ML, or related field, or equivalent practical experience.
Technically credible player-coach who can stay hands-on in code while managing and growing a team, especially in complex agentic AI systems.
Experienced in end-to-end agent lifecycle including orchestration, identity/authentication, observability, risk controls, and operating AI reliably at scale in production.
Able to engage effectively with cross-functional stakeholders including senior leadership, product, and research teams to influence strategy and delivery.