Software Engineering Manager , AgentOps

Drive the future of Agentic AI at Pearson as part of the AgentOps team. Inspire innovation. Empower learning.

Why Join AgentOps

• Work on cutting-edge agentic AI systems at enterprise scale

• Help build a symbiotic workforce of humans and AI agents

• Solve real business problems across enterprise

• Be part of shaping next-gen AI engineering practices

Why This Role Matters

Are you an Manager who leads from the front - still hands-on in the code but at your best when you grow the people around you Do you thrive at the intersection of platform engineering orchestration and operations

Join our AgentOps team and lead the group that builds and operates Pearsons internal agentic AI platform that runs agent crews across business units - with the reliability observability and governance that production demands.

This is a genuine player-coach role. You will set technical direction by - designing systems reviewing code and shaping how we build - while you hire coach and deliver through a high-performing team. Without this role agentic use cases stall between a promising prototype and a dependable production service and the engineers building them lack the direction and support to do their best work.

In this key position you turn Pearsons AgentOps platform strategy into practical business outcomes and through this help people realize the lives they imagine through learning.

What Youll Do

Lead & Grow the Team

• Hire coach and develop a team of AgentOps Forward Deployed Engineers owning performance growth and career progression.

• Foster an inclusive high-performing culture of continuous improvement strong engineering craft and psychological safety.

• Set clear goals run a healthy delivery cadence and remove blockers so the team ships with quality and speed.

Build & Ship the Platform (hands-on)

• Stay technically hands-on - lead design reviews and set the patterns and standards the team builds to.

• Take high-impact agentic use cases from prototype to production with reusable connectors shared services and clean crew hand-offs.

• Establish standardized practices for agent development orchestration and LLMOps across the team.

Operate & Observe

• Instrument crews end to end with observability traces cost tokens latency and error rates so teams can see and trust what agents do.

• Own the reliability performance and cost targets that keep agentic workloads dependable scalable and operationally ready in production.

Govern & De-risk Agentic Work

• Establish guardrails constraints and risk controls for agent-driven work from acceptance criteria to safe governed enterprise integration.

• Own the identity authentication and access model for agents and connectors separating credentials RBAC and audit.

• Ensure agent crews meet regulatory security and data-privacy requirements as they scale across business units.

Collaborate & Influence

• Manage intake prioritization and cross-team dependencies translating business needs into clear acceptance criteria for your team.

• Partner with product research cloud data science and engineering leaders across OCTO.

• Act as a trusted advisor to senior leadership on agentic AI capabilities trade-offs and operational risk.

Drive Innovation

• Stay ahead of emerging trends in agent orchestration multi-agent frameworks and LLMOps and evaluate them pragmatically.

• Pilot new tools and patterns that raise the platforms capability reliability and developer experience.
  

Who You Are

• A player-coach who leads by doing technically credible enough to earn your engineers trust and genuinely energized by growing them.

• A pragmatic operator who turns complex agentic systems into reliable production-ready services.

• A people leader who builds inclusive high-performing teams and gives clear kind direct feedback.

• A collaborator who influences across functions and thrives in ambiguity.
  

What You Bring

Selected on demonstrated capability not years.

• Has led coached or mentored engineers - as a manager tech lead or team lead - and is ready to own hiring performance and growth for a team.

• Builds LLM-powered systems AI agents or workflow automation in production and stays hands-on with the code.

• Strong Python and backend/platform engineering on cloud-native distributed systems.

• Have worked on agent orchestration or multi-agent frameworks (e.g. CrewAI LangGraph ADK) and LLM observability tooling.

• Expertise in one of the public cloud platforms (AWS/Azure/GCP)

• Understands the agent lifecycle end to end - orchestration identity/auth observability guardrails and operating AI reliably in production.

• Sets standards and designs with clear trade-off awareness across quality latency cost resilience and maintainability.

• Excellent communication and stakeholder-engagement skills from hands-on engineers to senior leadership.

• Bachelors or Masters in Computer Science AI/ML or a related field or equivalent practical experience.

Even better

• Experience productionizing Agentic Applications

• Versed with MCP A2A context engineering and HITL agent execution.

• AI observability and evaluation frameworks (Langfuse / LangSmith / Arize Phoenix).

• Fluent in AI-pair-programming (Cursor Claude Code) as a delivery mode and able to raise a teams floor with it.

What Youll Gain

• The chance to lead a team building enterprise agentic AI used across Pearson.

• Room to stay technical while you grow as a people leader.

• Opportunities to shape strategy and influence outcomes across OCTO.

• Access to cutting-edge tools platforms and thought leadership.