Engineering Manager, AI Engineering: Chat

## About the Role The Engineering Manager position at Gitlab is a critical role that involves leading a team of skilled engineers in developing and implementing AI-powered chat workflows. This role is integral to Gitlab's mission to revolutionize the software development lifecycle with cutting-edge AI technology. As an Engineering Manager, you will be responsible for guiding your team through the development process, ensuring that projects are completed efficiently and to the highest standard.

The successful candidate will have a strong technical background, excellent leadership skills, and the ability to communicate complex ideas effectively. They will be well-versed in the latest AI trends and technologies and have a proven track record of delivering high-quality products. This is a remote position, offering the flexibility to work from anywhere in the Americas or Canada.

Gitlab's engineering team is known for its collaborative and innovative approach to problem-solving. As an Engineering Manager, you will be part of a dynamic team that values open communication, continuous learning, and mutual respect. Your contributions will have a direct impact on the company's success and the future of software development.

## What You Will Do - Manage a team of experienced engineers to deliver high-quality AI-powered chat workflows - Partner with product and UX teams to define requirements and deliver AI features that meet customer needs - Participate in technical architecture and development work for systems that run AI agents at scale - Guide day-to-day execution by setting clear direction, tracking progress, and removing blockers - Coach engineers through feedback, guidance, and development conversations to foster growth and team performance - Promote a team culture grounded in curiosity, inclusion, accountability, and steady delivery against team goals - Improve quality, testing, and performance practices to increase coverage and reliability - Collaborate with cross-functional teams to identify and prioritize project requirements - Develop and manage project plans, resource allocation, and timelines - Ensure compliance with company standards, policies, and procedures

## What We Are Looking For - 5+ years of experience in software engineering, with a focus on AI and machine learning - Proven track record of leading high-performing teams and delivering complex projects - Strong technical skills in areas such as natural language processing, computer vision, or robotics - Excellent communication, leadership, and project management skills - Experience with agile development methodologies and version control systems - Strong understanding of cloud-based technologies and DevSecOps practices - Bachelor's degree in Computer Science, Engineering, or a related field

## Nice to Have - Experience with Gitlab's DevSecOps platform and Duo Chat - Knowledge of containers, Kubernetes, and cloud-native applications - Familiarity with CI/CD pipelines and automated testing frameworks - Certification in AI, machine learning, or a related field

## Benefits and Perks - Competitive salary and equity package - Comprehensive health, dental, and vision insurance - Flexible working hours and remote work options - Generous paid time off and holiday policy - Professional development opportunities and conference sponsorship - Access to cutting-edge technologies and tools - Collaborative and dynamic work environment

- Tip: Showcase your experience with AI-powered chat workflows and team management in your application.

• To stand out, highlight your achievements in delivering complex projects and leading high-performing teams.
• Be prepared to discuss your technical skills, such as natural language processing and computer vision, during the interview.
• Familiarize yourself with Gitlab's DevSecOps platform and Duo Chat to demonstrate your knowledge and interest in the company's technology.
• When negotiating salary, consider the company's equity package and benefits in addition to the base salary.
• Be wary of red flags such as unclear expectations, lack of communication, or unrealistic project timelines during the interview process.