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Lead AI Engineer

avomindBerlin, Berlin, Germany
Remote Full-time

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Experience Level

Manager

Qualifications

To excel in this role, candidates should possess:A robust background in AI and machine learning, with hands-on experience in deploying AI solutions. Proficiency in software development and engineering practices. Experience leading cross-functional teams, with a focus on collaboration and strategic alignment. Strong analytical and problem-solving skills. Familiarity with data governance and ethical AI practices.

About the job

About Our Client
Founded in Canada in 2015, our client has rapidly expanded to encompass a global portfolio of over 118 companies. They specialize in acquiring and developing vertical market software firms, empowering each business to deliver top-notch mission-critical solutions tailored to their industry's needs. A cornerstone of our client's philosophy is to invest in well-established enterprises while cultivating an entrepreneurial atmosphere that transforms these companies into industry leaders. Their strategic approach focuses on building long-term partnerships with existing management to create and enhance value.

About the Role

As the AI Engineering Lead, you will assume a pivotal leadership role in defining and executing the company's AI strategy. You will be responsible for the practical integration of AI across our client's engineering framework, enhancing internal development and testing processes to improve efficiency and quality. Additionally, you will oversee the development of AI-driven product features that provide tangible benefits to users. In this position, you will ensure alignment between engineering, product management, and data science teams, translating innovative ideas into actionable solutions and guiding teams to unlock their full potential through effective AI integration.

Key Responsibilities

  • AI Strategy & Vision: Develop a comprehensive AI roadmap that aligns with business objectives; identify opportunities for AI/ML applications in internal workflows (e.g., code generation, automated testing, monitoring); collaborate with product leadership to design and implement AI-enhanced product features.
  • AI Integration into Engineering Practice: Spearhead the deployment of AI tools within the Software Development Life Cycle (SDLC) (e.g., GitHub Copilot, CodeWhisperer, Tabnine); automate unit testing, static code analysis, and regression testing leveraging AI; guide the application of AI in CI/CD pipelines for improved monitoring, alerting, and predictive operations.
  • AI Product Development: Design and oversee the creation of AI/ML models and AI-enhanced product features; ensure adherence to best practices in AI/ML, including model training, data governance, validation, and ethics; select and manage the necessary infrastructure (e.g., cloud GPU/TPU, model operations platforms like MLflow or Vertex AI).
  • Team Leadership & Cross-Function Collaboration: Lead a team of AI engineers, data scientists, and MLOps personnel; collaborate with product, design, and stakeholders to ensure AI features align with user value; mentor engineering teams on responsible AI usage, prompt engineering, and model comprehension.
  • Governance & Compliance: Establish standards for responsible and explainable AI; ensure compliance with regulatory and ethical guidelines (e.g., GDPR, fairness, transparency); monitor model performance to prevent drift or unintended behaviors.

About avomind

Our client is a dynamic investment firm with a proven track record in the software industry, dedicated to enhancing the capabilities of its portfolio companies through innovative AI solutions.

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