Software Engineering Manager - AI Enablement and Developer Tooling

Servicing Technology builds and runs the systems Rocket Mortgage clients use to manage their mortgage after closing — payments, escrow, payoffs, and the support experiences around them. As Software Engineering Manager (AI Enablement and Developer Tooling), you will lead the team that builds the tooling, accelerators, and shared engineering systems that make it faster and safer for every team in the Organization to build and operate AI-powered software.

You remove friction for the engineering teams you support through self-service tooling, reusable patterns, automation, and strong feedback loops. This is a builder's role in a space that is still being defined: you will shape what this team owns, earn credibility with senior engineers, and influence architectural decisions well beyond your direct reports.
 

About the Role

• Lead, mentor, and grow a team that owns AI enablement, developer tooling, and reusable accelerators for Servicing Technology

• Stay hands-on — review code, prototype, and work with AI-assisted development yourself, setting the engineering quality bar by example rather than by directive

• Build the internal tools, automation, workflows, and reference implementations that remove friction and measurably improve engineering productivity across Servicing teams

• Drive real adoption of AI capabilities — shared patterns, evaluation, experimentation support, and production-readiness guidance — so teams ship AI-powered software confidently rather than experimentally

• Raise the bar on observability, resilience, incident learning, automation, and reduction of operational toil across Servicing Technology

• Turn ambiguous problems into clear ownership, decisions, and measurable outcomes, partnering with engineering, security, product, and senior leadership to align on AI strategy and infrastructure investment

About You
Minimum Qualifications

• Have led a team whose output was consumed by other engineering teams — a shared capability, tool, or platform — rather than a single application or an operational function

• Engineering leadership experience managing technical teams, including hiring, developing engineers, and setting technical direction

• Strong technical depth in distributed systems, cloud infrastructure, or software delivery — enough to challenge architecture and earn credibility with senior engineers

• Hands-on coding ability — you still write and review code, and can reason through a problem in a codebase alongside your engineers

• Credible, practical understanding of modern production AI: LLMs, RAG, agents, model APIs, evaluation, lifecycle management, governance, and cost

• Proven ability to create clarity in ambiguous spaces — establishing ownership, driving work through completion, and showing measurable outcomes

• Excellent communication and cross-team influence, with the ability to explain complex technical tradeoffs to engineers, security partners, product, and executives

Preferred Qualifications

• Built or led developer tooling, shared engineering capabilities, or developer productivity programs at scale

• Productionized AI or LLM capabilities, or led AI enablement initiatives across multiple engineering teams

• Drove measurable adoption of a shared capability across multiple teams — not just delivery of it

• Strong awareness of how the wider industry is solving these problems, with a track record of adapting proven practices thoughtfully rather than copying them; contributions to the broader engineering community (open source, writing, speaking, standards) are a plus

Also useful, though not required: agent frameworks, AI evaluation and tracing, model routing or inference-cost optimization, and AI security, governance, and safety practices.

The question we keep coming back to: show us something you built that materially changed how other engineers build or operate software.