Infrastructure Architect (AI or Big data)

We are looking for an experienced AI Infrastructure Architect for a banking client. The role is to design, build, and optimise the next‑generation platforms that power our enterprise AI and machine learning ecosystem. This is a strategic, high‑impact role for a technical leader who can bridge architecture, engineering, and operations to deliver scalable, secure, and high‑performance AI infrastructure.

Key Responsibilities

• • Design and architect end‑to‑end AI infrastructure, including compute, storage, networking, and orchestration layers for large‑scale ML workloads.
  • Lead the implementation of GPU‑accelerated platforms for training, inference, and model lifecycle management.
  • Develop cloud‑native and hybrid AI architectures leveraging Kubernetes, containerisation, and distributed systems.
  • Collaborate with data science and engineering teams to ensure infrastructure meets performance, scalability, and reliability requirements.
  • Establish best practices for MLOps, observability, and automation across the AI/ML pipeline.
  • Ensure compliance, security, and governance for AI workloads in a regulated environment.
  • Evaluate emerging AI technologies and drive adoption of modern tooling, frameworks, and accelerators.

Requirements

• Strong experience in AI/ML infrastructure architecture across cloud or on‑prem environments.
• Experience working on big data infrastructure including Hadoop, Hive, Spark, etc.
• Hands‑on expertise with Kubernetes, Docker, and distributed compute.
• Deep understanding of GPU platforms (NVIDIA, CUDA, NCCL, Triton, etc.).
• Experience with MLOps tooling such as MLflow, Kubeflow, Airflow, or similar.
• Knowledge of data platforms and pipelines supporting large‑scale AI workloads.

Interested candidates please email your latest resume to [email protected]