Software Engineering Team Manager

• 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.

You may be a good fit if you have

• 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.

• 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.