Manager, Software Engineering

RBGlobalBeverly Hills, CA
3h

About The Position

The Software Engineering Manager will lead a new Product Engineering team tasked with designing and building the next generation of Agentic AI-powered products for SmartEquip. While the core focus is product delivery, this team is pioneering SmartEquip’s AI-native ecosystem. Therefore, this highly technical, hands-on leader will architect the robust agent platform and backend microservices, while building the foundational end-to-end product platform required to scale, verify, deploy, secure, and monitor AI agents.

Requirements

  • Engineering Leadership: At least 3 years of experience managing engineers, with a proven ability to independently architect, problem-solve, and develop robust solutions.
  • Technical Stack: Polyglot full-stack background with in-depth, hands-on production expertise in Python. Proven experience building scalable backend microservices and RESTful APIs using frameworks like Django or Flask.
  • Modern Frameworks & Libraries: Highly knowledgeable in popular Python ecosystems, with specific expertise in data validation and API frameworks like Pydantic and FastAPI, which are critical for agent data structuring.
  • AI & Agentic Mastery: Deep experience with context engineering, designing agentic architectures, and building automated agent delivery pipelines. Proven ability to build, secure, and monitor production-ready retrieval systems (RAG). Extensive experience using and directing autonomous coding agents is expected.
  • Cloud Infrastructure: Experienced working with cloud platforms (GCP, AWS) and deploying AI workloads at scale, with specific preference for AI cloud platforms like Vertex AI.
  • Quality & Verification: Experienced with Test Automation and a strong understanding of how to build automated verification for AI outputs where accuracy has serious consequences.

Responsibilities

  • Product & Team Leadership: Manage multiple Product Engineering projects and a cross-functional engineering staff, including Python backend engineers, AI engineers, and Test Automation engineers.
  • Architectural Ownership: Architect, design, code, review and guide the team in developing scalable, efficient, and performant code for both the Agentic AI products, the backend microservices that power them, and the underlying platform required to scale and secure them.
  • AI-Native Development: Champion an AI-first approach by deeply integrating autonomous coding agents into the team's daily workflows and SDLC.
  • Intelligent Systems: Lead the development of intelligent retrieval systems—from RAG pipelines to agentic architectures that reason across multiple data sources.
  • Pipeline & Deployment: Work closely with DevOps/SRE to plan, shape, and own the team's end-to-end delivery process, ensuring robust deployment and monitoring for production AI and microservice systems.
  • Strategic Tooling: Evaluate and select the right agentic frameworks (e.g., LangGraph, CrewAI, MCP, Google ADK, A2A, Agent Stack) and tools, partnering with SmartEquip technical leadership. We prioritize a deep foundational understanding of AI ecosystems and model behaviors over transient framework hype, ensuring engineers are efficient and proactive.
  • Verification & Security: Build automated test and verification pipelines tailored for AI systems, operating with an accuracy-first mindset to manage hallucination risks and ensure secure data access.
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