Software Engineering Manager (Agentic AI Applications)

Rocket is a Detroit-based company providing digital solutions for complex transactions across mortgages, fintech, and real estate. The Software Engineering Manager will lead a team building agentic AI applications for mortgage clients while remaining hands-on in architecture, coding, and code review. The role also owns technical strategy, AI quality standards, hiring and coaching, and collaboration with product and business stakeholders.

Responsibilities:

• Lead a team of engineers building agentic AI capabilities such as agent orchestration, tool calling, retrieval-augmented workflows, and LLM-powered features
• Stay hands-on: contribute to architecture, write and review code, and build critical components alongside the team
• Own the technical strategy for the platform, balancing speed, scalability, maintainability, and business impact
• Set the standard for evaluation, observability, and guardrails for AI agents, ensuring reliability, safety, and measurable quality in production
• Hire, coach, and grow engineers, giving clear feedback and creating real growth paths for the team
• Partner with product, design, data, and business stakeholders to set priorities and translate ambiguous business needs into a clear roadmap
• Define how the team works: engineering practices, AI-native development workflows, code review culture, and delivery cadence
• Lead collaboration across distributed engineering teams, including partners in India

Requirements:

• 8+ years of professional software development experience, including 2+ years leading engineers as a manager or tech lead
• Strong hands-on experience building production software in languages such as C#, Java, Python, JavaScript, or TypeScript
• Experience designing and operating full-stack systems across frontend, backend, APIs, and data integrations on cloud platforms such as AWS, Azure, or Google Cloud
• Track record of hiring, coaching, and growing engineers
• Experience owning technical strategy or architecture for a product or platform
• Demonstrated ability to work with product and business stakeholders to set priorities and deliver outcomes
• Hands-on experience building with agentic AI frameworks (e.g., LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar), LLM APIs, or Model Context Protocol (MCP) tool integrations
• Experience with LLM application patterns such as retrieval-augmented generation (RAG), agent evaluation harnesses, guardrails, or production monitoring of AI behavior
• Experience leading a team through AI-native ways of working, such as AI coding agents, AI-assisted reviews, or multi-agent workflows
• Experience building or leading a team in a greenfield or newly formed product environment
• Experience with AWS, Kubernetes, CI/CD, automated testing, and production operations