Associate Director, Digital Measurement Platform & Systems Engineering

Description

The role sits in digital measurement, healthcare and new product work, and covers building platforms, systems, infrastructure, data pipelines and AI/ML deployment capabilities.

You will take engineering concepts from early testing to reliable, scalable production solutions, and you will be expected to move new technologies into real use quickly and at large scale.

Responsibilities

• Lead the move of platform, systems, infrastructure and AI/ML engineering work into production-ready solutions.
• Lead the design, build, testing, deployment and operation of production-grade platforms, backend services, data pipelines, machine learning deployment frameworks and automation systems that process complex, high-dimensional data.
• Lead platform, backend, cloud, data and deployment work across products and engineering initiatives.
• Evaluate new architectures, technologies and engineering approaches, and drive their adoption with software, data and machine learning engineers and architects.
• Provide technical leadership and mentoring to engineering teams while contributing hands-on to platform, data and AI/ML infrastructure.
• Improve the performance, scalability, reliability and operational efficiency of platform, data processing and machine learning production systems using a range of techniques.
• Lead testing and validation of platforms, systems, infrastructure and deployment capabilities to confirm they are ready for production.

Requirements

• A Master's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Artificial Intelligence or a related field.
• 10+ years designing, building and operating production-grade software platforms, distributed systems, cloud infrastructure, data pipelines and machine learning deployment environments.
• Hands-on experience building and running production backend services, distributed systems, data pipelines and cloud-native applications.
• Programming experience in Python, Java, C++ or equivalent.
• Experience with cloud-native platforms, Kubernetes, DevOps or MLOps practices, CI/CD pipelines and Infrastructure as Code.
• Experience deploying, scaling and supporting machine learning, data processing and analytics workloads in production.
• Experience with large-scale production systems, cloud environments and real-world datasets.
• Experience with release management, monitoring, observability, security and operational best practices.
• Proven record of leading engineering teams and delivering complex platform, data and cloud infrastructure initiatives.
• Experience leading technical solution delivery and working across engineering, data science, product and architecture teams.

Conditions

The potential base pay range, annualized, is €52,500.00 to €89,300.00. The actual offer may vary based on qualifications such as knowledge, skills, education and experience, location, and whether the role is full or part time.

Incentive plans, bonuses or other compensation may be offered depending on the position.

Benefits

• Health and welfare benefits and other benefits may be offered.