AI Engineering Lead

About our client

Established in Canada in 2015, our client has grown to a global portfolio of 118+ companies, acquiring and developing vertical market software companies, enabling each business to deliver the best mission-critical solutions for customers in their respective industries. A key tenet of our client's philosophy is to invest in well-established businesses and foster an entrepreneurial environment that molds companies into leaders in their respective industries. Our client looks to buy, hold and create value through long-term partnerships with existing management.

About the role

The AI Engineering Lead plays a critical leadership role in shaping and executing the company's AI strategy and is responsible for the practical application of AI across our client's engineering landscape. This includes integrating AI into internal development and testing processes to boost efficiency and quality, as well as overseeing the creation of AI-enabled product features that deliver real user value. In this role, you’ll lead the execution of our client's AI strategy, ensuring alignment across engineering, product, and data science. You’ll act as a connector between these functions—translating ideas into solutions, and helping teams turn potential into performance through smart, scalable AI adoption.

Key responsibilities

• AI Strategy & Vision : Define the overall AI roadmap aligned with business goals; Identify opportunities to use AI / ML in internal workflows (e.g., code generation, automated testing, monitoring); Partner with product leadership to define and build AI-powered product features.
• AI Integration into Engineering Practice : Lead the implementation of AI tools in the SDLC (e.g., GitHub Copilot, CodeWhisperer, Tabnine); Automate unit testing, static code analysis, or regression testing using AI; Guide AI use in CI / CD pipelines for smarter monitoring, alerting, and predictive ops.
• AI Product Development : Architect and oversee development of AI / ML models and AI-enhanced product features; Ensure best practices in AI / ML : model training, data governance, validation, and ethics; Select and manage infrastructure (e.g., cloud GPU / TPU, model ops platforms like MLflow or Vertex AI).
• Team Leadership & Cross-Function Collaboration : Lead AI engineers, data scientists, and MLOps roles (or coordinate with them across teams); Collaborate with product, design, and stakeholders to align AI features with user value; Mentor engineering teams in responsible AI usage, prompt engineering, and model understanding.
• Governance & Compliance : Define standards for responsible and explainable AI; Ensure regulatory and ethical compliance (e.g., GDPR,fairness, transparency); Monitor model performance and prevent drift or unintended behavior.

The successful candidate can be based anywhere — with the flexibility to collaborate both remotely and on-site in Berlin as needed.

Requirements

Ready to join a collaborative and innovative team where you can make an immediate impact?