Engineering Manager

As an Engineering Manager at Robin AI, your primary responsibilities include leading the Search team to develop advanced legal search and recommendation systems. You will oversee the technical strategy for our search and agent orchestration infrastructure, mentor your team, and collaborate with Product and Machine Learning teams to ensure we deliver top-notch AI solutions.

To be considered for the Engineering Manager role at Robin AI, candidates should possess over 5 years of engineering experience, with a minimum of 2 years in a leadership capacity. Ideal candidates will also have experience with machine learning applications in production environments and a proven track record of successfully delivering complex technical projects.

The culture at Robin AI is grounded in creativity, collaboration, and support. As an Engineering Manager, you can expect a high-trust environment that encourages autonomy, allowing you and your team to take risks and innovate. We believe in empowering our employees to set ambitious goals and providing the resources and support needed to achieve them.

Robin AI is dedicated to the professional growth of its employees. For Engineering Managers, there's a strong emphasis on personal development through mentorship programs and promotion opportunities for high performers. The company actively fosters a culture of continuous learning and improvement, tailoring career development to individual aspirations.

Engineering Managers at Robin AI enjoy a competitive range of benefits, including a flexible hybrid working schedule, an attractive equity package, comprehensive health insurance, mental health resources, and gym discounts. Additionally, you'll have 25 days of paid time off, plus bank holidays, ensuring a healthy work-life balance.

When approaching technical strategy, I focus on aligning team objectives with the overall business goals. I facilitate open discussions with my team to gather insights, balance technical feasibility with user impact, and stay updated on industry trends to ensure we remain competitive in delivering innovative solutions.

I have substantial experience deploying machine learning models in production, having collaborated closely with data scientists to develop robust ML pipelines. My approach emphasizes ensuring data quality, model validation, and implementing feedback loops for continuous improvement while monitoring performance post-deployment.

Handling team conflicts requires a balance of empathy and assertiveness. I engage in one-on-one discussions with the involved parties to understand their perspectives, facilitate mediation sessions if necessary, and encourage open communication to foster a collaborative resolution, ensuring the team moves forward positively.

I prefer a coaching leadership style, focusing on empowering my team members by encouraging them to take ownership of their work while providing guidance and support. This approach fosters a culture of trust and innovation, enabling team members to flourish and take on challenging projects.

Certainly! One of the most complex projects I managed was implementing an end-to-end AI-driven recommendation system. It involved coordinating cross-functional teams, defining clear milestones, and aligning technical deliverables with business objectives, ultimately leading to a significant increase in user engagement and satisfaction.

I prioritize tasks based on alignment with strategic priorities, deadlines, and team capacity. Utilizing frameworks like the Eisenhower Matrix helps differentiate between urgent and important tasks, ensuring we focus on high-impact projects while keeping the team engaged and productive.

To ensure ongoing professional development, I promote a culture of continuous learning by encouraging attendance at conferences, workshops, and relevant training sessions. I also facilitate knowledge-sharing sessions within the team and encourage individual pursuits of certifications aligned with our tech stack.

I measure success not just by the completion of projects but also by the team’s engagement and satisfaction levels. Regular progress reviews, feedback surveys, and key performance indicators like code quality, development speed, and innovation output help gauge the team's effectiveness.

Staying updated is crucial, so I allocate time weekly for reading industry publications, participating in webinars, and engaging with professional networks. I also encourage the team to share interesting articles and innovations they come across, fostering a collaborative learning environment.

I am motivated by the opportunity to lead a talented team toward innovative solutions that can significantly impact the legal industry. Seeing my team’s growth, the success of our projects, and the positive influence we have on our clients drives my passion for the role.