Engineering Manager, AI & Infrastructure - Fully Remote, Turkey Based

Appier; Fatih; Remote; TRY 3,327,000 - 4,992,000; Full time

Job summary

A leading technology company based in Turkey is seeking an experienced Engineering Manager to lead a high-performing engineering team. The ideal candidate will have over 4 years of software engineering experience and at least 2 years in a leadership capacity. This fully remote role requires strong technical expertise in DevOps principles and modern cloud infrastructure, as well as excellent communication skills.

Qualifications

• 4+ years of hands-on software engineering experience, including 2+ years in a leadership role.
• Experience leading cross-functional teams in fast-paced environments.
• Solid understanding of modern cloud infrastructure (e.g., AWS, GCP, Azure).

Responsibilities

• Lead, mentor, and scale a team of engineers across infrastructure and MLOps.
• Collaborate with product and machine learning teams to align efforts.
• Oversee project planning and promote engineering excellence.

Skills

Software engineering experience

Leadership

DevOps principles

Cloud infrastructure

Communication

Tools

GitHub Actions

Terraform

Kubernetes

Job description

Engineering Manager, AI & Infrastructure - Fully Remote, Turkey Based

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

AdCreative.ai, 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 industry's future, making campaigns faster, smarter, and more impactful.

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

• Lead, mentor, and scale a team of engineers working across infrastructure, backend services, DevOps platforms, and MLOps
• Collaborate with product, data, and machine learning teams to align engineering efforts with business goals
• Oversee project planning, prioritization, and delivery with a focus on quality and velocity
• Promote engineering excellence by establishing best practices in code quality, testing, deployment, and observability
• Drive initiatives in system scalability, reliability, and maintainability
• Contribute to infrastructure decisions, ensuring efficient CI/CD pipelines and DevOps tooling
• Support and evolve MLOps pipelines in collaboration with ML engineers and data scientists

About you

• 4+ years of hands-on software engineering experience, including at least 2+ years in a leadership or management role
• Proven experience leading cross-functional technical teams in fast-paced environments
• Solid understanding of DevOps principles and modern cloud infrastructure (e.g., AWS, GCP, Azure)
• Familiarity with CI/CD tools (e.g., GitHub Actions, ArgoCD, Jenkins), infrastructure as code (e.g., Terraform, Pulumi), and container orchestration (e.g., Kubernetes)
• Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders

Preferred qualifications

• Experience with MLOps workflows (model training, deployment, monitoring, data pipelines)
• Background in machine learning infrastructure or working with ML engineering teams
• Exposure to data platforms, versioning tools (e.g., DVC), or ML orchestration frameworks (e.g., Kubeflow, MLflow)
• Ability to guide architectural decisions involving machine learning systems in production

We are an equal opportunities employer and welcome applications from all qualified candidates.