Manager, Software Engineering & Development

Position Summary

As a Software Engineering Manager, Enterprise AI Platform
, you will lead a team responsible for building, operating, and continuously improving production‑grade AI‑enabled software.

This role manages a cross‑functional engineering team that may include:

• Software Engineers
• SDETs
• Dev Ops Engineers
• Support Engineers

This is a hands‑on engineering leadership role for someone who has strong software engineering experience, cares deeply about people development, and can help teams deliver practical AI‑powered solutions with speed, quality, and discipline.

While this is a management role, the person in this position is expected to stay close to the codebase and technical workflow. When the situation calls for it, they may contribute directly to implementation, debugging, automation, technical spikes, or code reviews to help the team move faster, remove blockers, or solve critical problems.

You will be responsible for:

• Growing and developing engineering talent
• Creating a high‑performance team culture
• Supporting delivery of enterprise AI platform capabilities
• Improving engineering practices across software development, testing, Dev Ops, support, and operations
• Partnering with product, architecture, AI, business, and technology leaders
• Helping the team move quickly while maintaining quality, security, reliability, and maintainability
• Occasionally contributing hands‑on to implementation, debugging, automation, technical spikes, or code reviews when the situation calls for it

This role is ideal for an emerging engineering leader who has already demonstrated strong technical leadership and people leadership potential, and who is looking to continue growing and evolving their career.

We are looking for someone who can lead through influence, coach engineers effectively, improve team execution, and help build the operating model for modern AI‑enabled software delivery.

We are looking for a manager who can balance people leadership
, technical judgment
, and delivery execution
.

The ideal candidate is someone who:

• Has a strong software engineering background
• Understands how modern software teams build, test, deploy, and operate production systems
• Can coach software engineers, SDETs, Dev Ops engineers, and support engineers
• Stays technically engaged with the team’s codebase, architecture, development workflow, and operational tooling
• Knows when to guide, when to delegate, and when to contribute hands‑on to help the team move forward
• Knows how to create clarity in ambiguous environments
• Can translate business and platform goals into team execution
• Has strong instincts around quality, automation, observability, reliability, and supportability
• Is comfortable working in a fast‑moving AI environment
• Can partner well with product owners, architects, data scientists, business stakeholders, and senior leaders
• Wants to grow into broader engineering leadership responsibility over time

This is a software engineering management role focused on building and growing the team that delivers and operates the Enterprise AI Platform.

• 5+ years of professional software engineering or related technical experience.
• 2+ years of technical leadership, team leadership, people leadership, or engineering management experience.
• Experience leading, coaching, or mentoring software engineers or related technical team members.
• Ability and willingness to stay technically engaged with the team’s codebase, architecture, development workflow, and operational tooling, including occasional hands‑on contribution when needed.
• Strong understanding of modern software engineering practices, including:
  • Clean code
  • Source control
  • Unit testing
  • CI/CD
  • Design patterns
  • Refactoring
  • Maintainability
  • Production support
• Experience working with software delivery teams that include roles such as:
  • Software Engineers
  • SDETs
  • Dev Ops Engineers
  • Support Engineers
  • Quality Engineers
• Experience supporting production software systems, including troubleshooting, incident response, root‑cause analysis, or operational improvement.
• Strong understanding of Agile delivery practices and modern engineering team workflows.
• Ability to develop associates through coaching,…