[Hiring] Software Engineering Team Manager @Pearson

Role Description

PSG-CP is in need of a leader who can help manage our global team of engineers to help our lines of business receive the content they need to power their applications. The engineering team is embedded directly with our most strategic internal businesses and ship production AI applications against real problems. Running software, not decks or specs. As this practice grows, we need a founding leader to build and scale it.

This role leads four teams at the heart of the PSG-CP platform: Prizm, Semantics, Transformation, and Delivery Services. These are the groups that own how content is structured, semantically enriched, transformed, and delivered at global scale. Your job is to lead them forward while changing how they work: closer to the businesses they serve, faster from "we need something that does X" to "here, try this," and increasingly built around frontier AI.

You will hire and develop a strong group of engineers and set the technical and operational bar for engagements with lines of business, and build the playbooks that turn one-off wins into repeatable patterns. This is a player-coach role with a strong bias toward leadership. You will stay close enough to the technical work to review architectures, debug production issues, and pair with your team when it matters, but your primary impact will come from the people you hire, the standards you set, and the culture you create. You will partner with Product, Architecture, and leaders across Pearson's lines of business to shape how the content platform evolves, and your team's field insights will directly influence platform direction.

Responsibilities

• Set a high bar for technical talent, customer instincts, and AI-first engineering judgment.
• Conduct regular 1:1s, provide technical mentorship, and invest in the career growth of each team member. Create an environment where strong engineers do the best work of their careers.
• Staff and oversee engagements with lines of business across your team's portfolio, making resource allocation decisions that balance stakeholder needs, platform health, team development, and business priorities.
• Own delivery across the Prizm, Semantics, Transformation, and Delivery Services roadmaps, keeping the core platform reliable, scaled, and moving.
• Work with line-of-business leaders to qualify engagements, scope work, and set expectations before your team commits. Own the relationship through the lifecycle of the engagement, not just the kickoff.
• Review technical architectures and code produced by your teams, ensuring they ship high-quality, production-ready solutions that meet enterprise expectations for reliability, observability, security, and cost.
• Stay hands-on enough to lead technical discovery sessions, prototype solutions, and debug complex production issues alongside your team when needed.
• Build repeatable playbooks, starter repositories, integration templates, and an internal knowledge base that captures what your team learns in the field. Route field-proven patterns back into the platform teams so wins compound instead of staying one-off.
• Set and uphold a high standard for AI-augmented engineering practice. Coach the team on the effective, responsible use of agentic coding tools, and shape how AI fits into how this group designs, ships, and operates software.
• Define team OKRs that tie to line-of-business outcomes and platform adoption goals. Create operational cadences (standups, retros, engagement reviews, design reviews, incident reviews) that keep the teams aligned, accountable, and continuously improving.
• Partner with Product and Architecture to translate field insights into platform improvements. Serve as the voice of the internal customer in planning.
• Represent the platform with senior stakeholders across lines of business at the highest level.

Qualifications

• 10+ years of experience in software engineering, solutions architecture, or a technical customer-facing role such as forward deployed engineering or consulting.
• 4+ years of people management experience with a track record of hiring, developing, and retaining strong engineers, ideally within a services, post-sales, or forward deployed organization.
• Experience building teams or practices from 0 to 1, plus the judgment to do that inside an organization with real systems already in production.
• Experience working directly with enterprise stakeholders on technical implementations, including comfort navigating complex organizational dynamics in a large company.
• Real production experience building on large language models and generative AI: agents, retrieval, evaluation frameworks, prompt management, guardrails, and the harder operational realities of running AI in production (rate limits, non-determinism, provider outages, schema drift, cost and latency).
• A genuine point of view on AI-first engineering. You use agentic coding tools daily, you have opinions on which tools work best for which tasks, and you have shaped team practice around responsible AI adoption.
• Enough depth in distributed backend systems and cloud-native architectures (AWS, Azure, or GCP) to credibly review what your teams ship: services, async processing, event-driven pipelines, and content and data systems at scale.
• Strong operational instincts around observability, on-call, incident response, security, and the kind of platform discipline that keeps services trustworthy at multi-tenant scale.
• Executive presence and the ability to move between strategic conversations with senior stakeholders and hands-on debugging sessions with engineers without losing either audience.
• Strong written and verbal communication skills. You can translate technical complexity into clear narratives for different audiences.
• Genuine excitement about building something new and defining what great looks like for a practice that doesn't yet exist.

Logistics

• Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience.
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. The full-time salary range is between $170,000 - $190,000. This position is eligible to participate in an annual incentive program, and information on benefits offered is here.

Applications will be accepted through 26th July 2026. This window may be extended depending on business needs.