Senior Manager, Associate Director, Enterprise Integration Architect

Application Development & Integration – Event-Driven Architecture and AI

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We are seeking a highly skilled Enterprise Integration Architect with certified, hands‑on expertise in Apache Kafka and strong experience embedding AI capabilities into real‑time, event‑driven platforms. This pivotal role involves architecting streaming data platforms that power both operational systems and AI/ML applications, while leveraging AI tools and techniques to enhance the architectural design and delivery process itself.

As an Enterprise Integration Architect, you will be accountable for defining the technical vision and architectural strategy for Kafka‑based event streaming platforms and their integration with AI‑enabled applications. You will lead end‑to‑end solution design, from conceptualisation through to production deployment, ensuring platforms are scalable, secure, low‑latency, and aligned with overall business objectives.

Your role will involve translating business requirements into robust event‑driven architectures, including topic and schema design, stream processing pipelines, and real‑time feature delivery for AI/ML models, while selecting appropriate technologies and guiding engineering teams through implementation.

You will be instrumental in establishing architectural best practices for Kafka platform design, data governance, and streaming AI patterns, and in championing innovative approaches to leveraging AI within event‑driven architectures. You will work closely with clients, product owners, data scientists, and engineering teams to deliver high‑impact, real‑time AI solutions.

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Responsibilities:

• Lead the architectural design, development, and implementation of complex Kafka‑based event‑driven platforms and AI‑driven applications across various business domains.
• Define and enforce architectural principles, standards, and best practices for Kafka cluster design, topic/schema management, and stream processing, ensuring scalability, security, and maintainability.
• Translate business requirements and use cases into comprehensive technical architectures, including event models, integration patterns, and deployment strategies for streaming and AI applications.
• Evaluate and recommend appropriate streaming and AI technologies, platforms, and frameworks, including Kafka Streams, ksqlDB, Apache Flink, Schema Registry, and real‑time feature stores for ML/AI use cases.
• Strategically utilise AI‑powered tools and techniques (e.g., generative AI for code, architectural pattern suggestions, anomaly detection on streaming data) to accelerate and enhance architectural design, documentation, and development processes.
• Design and oversee real‑time data pipelines that support AI/ML model training and inference, including feature engineering, model serving triggers, and event‑driven GenAI use cases.
• Provide technical leadership and mentorship to development teams, guiding them through architectural decisions and complex technical challenges related to Kafka and AI