Software Engineering Manager - AI

Pearson•Hoboken, NJ

7h•$150,000 - $175,000•Hybrid

About The Position

We are seeking an AI Engineering Manager to lead and scale our Agentic Workflow engineering organization within the Pearson Learning Studio (PLS) product. This leader will oversee a team of 5+ engineers, driving both technical excellence and strong people leadership in a globally distributed environment (India and Sri Lanka). This role is ideal for a leader who thrives at the intersection of people development, execution at scale, and data-driven product engineering. You will be responsible not just for delivery, but for building a high-performing, engaged engineering organization.

Requirements

5+ years of engineering leadership experience, including managing teams of 5+ engineers.
8+ years of overall experience in software engineering.
Proven experience scaling and leading distributed engineering teams across geographies.
Strong technical background in: SQL & data analytics systems, ReactJS, Java-based backend systems.
Demonstrated success in delivering data-driven platforms or analytics products.
Strong experience with Agile/Scrum at scale.
Excellent communication, stakeholder management, and organizational leadership skills.
Bachelor’s degree in Computer Science, Engineering, or related field.

Nice To Haves

Experience building or leading high-performing engineering organizations at scale.
Experience in education technology and Learning science.
Familiarity with cloud platforms (AWS, Azure, or GCP).
Experience with data visualization and analytics frameworks.

Responsibilities

Lead, manage, and scale a distributed engineering team of 5+ engineers, including senior engineers and team leads.
Build a strong leadership bench by mentoring tech leads and emerging managers.
Drive performance management, including goal setting, regular feedback, and career development plans.
Foster a culture of ownership, accountability, psychological safety, and continuous learning.
Manage hiring, onboarding, and team capacity planning to support business growth.
Ensure high levels of team engagement, retention, and productivity across geographies.
Own end-to-end delivery for the Insights & Recommendations domain.
Establish predictable execution rhythms, ensuring on-time, high-quality releases.
Partner with Product, Design, and Analytics to translate strategy into clear engineering roadmaps.
Identify risks early and proactively remove organizational, technical, or process bottlenecks.
Drive operational excellence, including metrics, KPIs, and continuous improvement initiatives.
Provide architectural oversight for data-driven applications, analytics pipelines, and web platforms.
Guide teams on best practices in SQL, data systems, ReactJS, and Java-based services.
Ensure scalable system design, performance optimization, and reliability.
Lead technical design reviews and promote sound engineering decisions across teams.
Balance hands-on involvement (as needed) with effective delegation to senior engineers and tech leads.
Champion Agile best practices across multiple teams (planning, backlog management, retrospectives).
Align engineering efforts with business outcomes and customer impact.
Collaborate with global stakeholders across time zones with strong communication discipline.
Drive transparency through clear reporting, stakeholder updates, and data-driven decision-making.