Engineering Manager, Agentic AI

Robinhood Robinhood · Fintech · Menlo Park, CA · ENG Data and AI Platform Division

Engineering Manager for the Agentic AI team at Robinhood, focused on building and scaling foundational AI/ML infrastructure and LLM-powered products for the fintech domain. The role involves leading a team of engineers and applied ML specialists, guiding model development and evaluation, and partnering cross-functionally to deliver AI-driven features.

What you'd actually do

  1. Lead, mentor, and scale a high-performing organization of engineers, managers, and applied ML specialists, providing technical guidance, regular feedback, and support for career growth.
  2. Guide model development and evaluation, ensuring AI applications are highly performant, secure, and ready to serve millions of customers.
  3. Partner cross-functionally with product, design, infrastructure, and other executive leaders to ensure AI platforms meet the complex needs of Robinhood’s diverse business lines.
  4. Establish clear engineering processes to ensure reliable delivery, code quality, and system scalability across multiple teams.

Skills

Required

  • Engineering leadership experience
  • Mentoring and scaling engineering teams
  • Applied Machine Learning
  • Productionizing LLMs and advanced models
  • ML infrastructure and platforms
  • Deploying AI safely and securely
  • Cross-functional partnership
  • Process establishment for reliable delivery, code quality, and scalability

Nice to have

  • Experience with agentic AI systems
  • Experience in fintech domain

What the JD emphasized

  • in-person attendance expected 5 days per week
  • strong software engineering background
  • deep expertise in applied ML at scale
  • Proven engineering leadership experience
  • track record of supporting performance, hiring top talent, managing managers, and driving organizational development
  • Hands-on experience in Applied Machine Learning
  • productionizing applications that leverage LLMs and advanced models to build real-world products
  • Deep understanding of ML infrastructure, platforms, and the complexities of deploying AI safely and securely across an enterprise
  • execution-focused mindset

Other signals

  • building foundational AI and ML infrastructure
  • empowers product and engineering teams to seamlessly build, deploy, and scale AI-driven features
  • oversee the creation of multiple ML and AI models spanning Robinhood products, and internal optimizations
  • guide the engineering organization in producing advanced models and leveraging Large Language Models (LLMs) to create real, scalable products
  • productionizing applications that leverage LLMs and advanced models to build real-world products
  • deep understanding of ML infrastructure, platforms, and the complexities of deploying AI safely and securely across an enterprise