About Appier  Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About AdCreative.ai team <a href="https://www.adcreative.ai/?__hstc=236978142.da388cfbfee99accec0744b9cd8448d8.1750667944075.1750673958881.1750752905443.3&amp;__hssc=236978142.3.1750752905443&amp;__hsfp=3455874677&amp;_fsi=J4uiLrdy&amp;_fsi=J4uiLrdy">AdCreative.ai</a>, based in Paris, France, is a leading AI-driven platform revolutionizing how businesses create advertising and marketing assets. By combining proprietary AI models, advanced technology, and a user-centric approach, AdCreative.ai empowers brands to generate high-performing ad creatives that deliver measurable ROI. Founded in 2021 and trusted by global brands like Snapchat, Pernod Ricard, Reckitt, BNP Paribas and Chopard, the platform merges cutting-edge AI technology with advertising expertise to shape the industrys future, making campaigns faster, smarter, and more impactful. As a trusted partner in the AI era, AdCreative.ai offers innovative tools like Creative Insights, AI Video Ad Generation, and Stock Image Creation, enabling businesses to scale with precision and achieve creative excellence in their campaigns. About the role We are seeking an experienced and visionary Engineering Manager to lead and grow a high-performing engineering team. This role requires a balance of strong technical expertise, people leadership, and strategic thinking to drive product and infrastructure initiatives forward. The ideal candidate has a deep background in backend or systems engineering, a solid understanding of DevOps practices, and—preferably—experience with MLOps workflows in production-grade machine learning environments. Responsibilities  <ul> <li>Lead, mentor, and scale a team of engineers working across infrastructure, backend services, DevOps platforms, and MLOps</li> <li>Collaborate with product, data, and machine learning teams to align engineering efforts with business goals  </li> <li>Oversee project planning, prioritization, and delivery with a focus on quality and velocity  </li> <li>Promote engineering excellence by establishing best practices in code quality, testing, deployment, and observability  </li> <li>Drive initiatives in system scalability, reliability, and maintainability  </li> <li>Contribute to infrastructure decisions, ensuring efficient CI/CD pipelines and DevOps tooling  </li> <li>(Preferred) Support and evolve MLOps pipelines in collaboration with ML engineers and data scientists</li> </ul> About you  [Minimum qualifications] <ul> <li>4+ years of hands-on software engineering experience, including at least 2+ years in a leadership or management role  </li> <li>Proven experience leading cross-functional technical teams in fast-paced environments  </li> <li>Solid understanding of DevOps principles and modern cloud infrastructure (e.g., AWS, GCP, Azure)  </li> <li>Familiarity with CI/CD tools (e.g., GitHub Actions, ArgoCD, Jenkins), infrastructure as code (e.g., Terraform, Pulumi), and container orchestration (e.g., Kubernetes)  </li> <li>Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders </li> </ul> [Preferred qualifications] <ul> <li>Experience with MLOps workflows (model training, deployment, monitoring, data pipelines)  </li> <li>Background in machine learning infrastructure or working with ML engineering teams  </li> <li>Exposure to data platforms, versioning tools (e.g., DVC), or ML orchestration frameworks (e.g., Kubeflow, MLflow)  </li> <li>Ability to guide architectural decisions involving machine learning systems in production</li> </ul> #LI-Fully Remote