As an Enterprise Integration Architect, you will shape Kafka-based, real-time data platforms and embed AI capabilities into AI-enabled applications. You will define the technical vision and lead end-to-end design from concept to production, ensuring scalability, security and low latency. You will collaborate with product owners, data scientists and engineering teams to deliver high-impact streaming and AI solutions. This role offers exposure to cutting-edge technologies and a chance to influence architectural patterns and governance. You’ll work in a collaborative, values-driven environment with a clear focus on measurable impact.
Pay / Benefits
training and skill development platforms (A Cloud Guru, Udemy, LinkedIn Learning)
certifications and training programmes
flexible/hybrid working
support for work-life balance
opportunity to work with cutting-edge technology
career development and growth
Responsibilities
Lead design, development and deployment of complex Kafka-based event-driven platforms and AI-powered applications across multiple business domains.
Define architectural principles and governance for Kafka clusters, topics, schemas, and streaming processes with a focus on security and maintainability.
Translate business needs into architectures including event models, integration patterns, and deployment strategies for streaming and AI applications.
Evaluate technologies such as Kafka Streams, ksqlDB, Apache Flink, Schema Registry, and real-time feature stores for ML/AI use cases.
Utilize AI-powered methods to accelerate design, documentation, and development processes (e.g., GenAI for code and pattern suggestions).
Design real-time data pipelines supporting AI/ML training and inference, including feature engineering and event-driven triggers.
Provide technical leadership and mentorship on Kafka and AI solution delivery.
Ensure data privacy, ethical AI and regulatory compliance (GDPR, AI Act); enforce Kafka security best practices.
Key requirements
Proven experience in Senior Integration or Solution Architect roles focused on Kafka-based platforms and AI-driven applications.
Strong hands-on experience with Apache Kafka, Kafka Connect, Kafka Streams, ksqlDB, Schema Registry, and Confluent Platform / Confluent Cloud.
Knowledge of generative AI models and real-time AI integration in event-driven designs.
Experience with stream processing frameworks (Kafka Streams, Apache Flink, Spark Structured Streaming) and ML/AI frameworks (TensorFlow, PyTorch) for real-time inference.
Familiarity with cloud platforms (AWS, Azure, GCP) and data governance, security best practices for Kafka/AI solutions.
Experience running Kafka on Kubernetes (Strimzi) and observability tools (Prometheus, Grafana, Confluent Control Center).
Strong communication and stakeholder management; ability to mentor teams and contribute to business development.
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