Senior Engineering Manager, Agentic AI

As a Senior Engineering Manager, Agentic AI at Robinhood, your primary responsibilities will include designing, building, and deploying AI applications. You'll manage a team of talented engineers, work collaboratively with various departments, identify pressing machine learning issues, and ensure timely delivery of solutions. This role requires strategic planning and prioritization, along with hiring top AI talent to scale the team effectively.

To be considered for the Senior Engineering Manager, Agentic AI position at Robinhood, you should have a graduate degree in a quantitative field, strong technical expertise in AI, proficiency with programming languages like Python or C++, and substantial experience in managing AI engineering teams. Additional expertise in ethical AI and familiarity with cloud platforms will be advantageous.

At Robinhood, the work environment for a Senior Engineering Manager, Agentic AI is vibrant and collaborative. You can expect a supportive atmosphere that fosters innovation, education, and mutual respect among diverse team members. The office features catered meals, fully stocked kitchens, and a focus on personal wellness, ensuring a balanced work-life dynamic.

Robinhood supports professional growth for a Senior Engineering Manager, Agentic AI through initiatives such as an annual lifestyle wallet for learning and development. They encourage continuous learning and skills enhancement in a collaborative environment, making it easier for leaders to stay on top of trends and technologies in AI.

Robinhood fosters an inclusive workplace for Senior Engineering Managers by embracing diversity across all backgrounds and experiences. The company is committed to building a workforce that represents various perspectives and skills, ensuring that everyone has equal opportunities to contribute and thrive.

In your response, highlight your previous roles managing AI teams, specifically mentioning metrics or projects that showcase your leadership. Discuss how you helped your team meet goals while fostering a culture of innovation and learning.

Detail your process for designing AI applications, including any frameworks or methodologies you utilize. Discuss the importance of understanding user needs and your experience with different AI paradigms.

Mention specific techniques you’ve implemented in past projects, such as reinforcement learning or supervised learning, and how they addressed particular challenges. Provide examples of outcomes and learnings.

Explain your prioritization strategy, focusing on how you align projects with the company's goals and consider resource availability. Share examples of effective prioritization that led to successful project outcomes.

Discuss your approach to recruitment, including where you source candidates and how you assess both technical and cultural fit. Share any specific successes or unique initiatives you've undertaken in hiring.

Describe the communication methods and collaboration tools you employ to bridge gaps between engineering, product, and design teams. Provide examples of successful cross-functional projects you've led.

Share a detailed example of a project, focusing on your role, the challenges faced, and the solutions you implemented. Highlight the impact this project had on your organization.

Mention resources you rely on, such as conferences, webinars, or professional networks. Stress the importance of continuous learning and adapting to new technologies and practices.

Discuss specific challenges you encountered in past deployments, how you approached these issues, and the lessons you learned. Highlight your problem-solving skills and adaptability.

Share specific actions you've taken to promote an innovative culture, such as brainstorming sessions, hackathons, or feedback loops. Explain how you encourage team members to contribute ideas freely.