Director Engineering - Team Lead

About the role

The Director Engineering- Team Lead will lead a team responsible for developing AI-enabled marketing platforms, focusing on scalable, reusable data capabilities and real-time decisioning systems in cloud and AI environments. The role involves defining platform vision, architecting cloud-native systems optimized for AI workflows, ensuring data reliability and precision, and collaborating across departments to meet business goals. The Director Engineering will serve as a key partner to Data engineers, AI/ML engineers, product managers, and external technical teams, to build real-time data pipelines and decisioning frameworks, enabling automated intelligent marketing workflows.

Responsibilities

• Define and execute the platform vision as a product, with clear adoption, usability, and business impact goals; build reusable, scalable capabilities for self-service data access, segmentation, and activation; establish standardized integration patterns across data, cloud, CRM and media ecosystems.
• Architect systems optimized for AI-driven and agentic workflows, including real-time decisioning and orchestration; enable intelligent audience creation, activation pathways, and automated optimization across CRM and media; build data pipelines and services that support scalable AI/ML use cases and continuous learning systems.
• Lead, mentor, and scale a high-performing team of engineers with strong ownership and execution discipline; stay close to architecture and critical technical decisions while empowering team autonomy; drive engineering excellence across system design, code quality, and reliability.
• Design and evolve distributed, cloud-native and AI-forward systems that are scalable, secure, and highly available; lead architecture across data platforms, APIs, integrations, and activation pipelines; ensure systems meet enterprise standards for resilience, performance, and compliance.
• Own end-to-end delivery of platform capabilities — from architecture through deployment and adoption; establish best practices in CI/CD, and automation; define and track key metrics: data accuracy, deployment velocity, and speed to activation.
• Partner with Product, Data, Marketing, and external platforms to translate business needs into scalable systems; influence decisions across a matrixed organization and communicate complex technical concepts clearly to executive stakeholders.

Requirements