AI Platform Engineer / Senior Consultant Specialist

• Design, build, deploy, and operate AI-enabled solutions that deliver measurable business outcomes.
• Build and productionise AI/ML solutions (predictive modelling, NLP, intelligent automation) aligned to product goals.
• Develop and maintain AI services and APIs for model inference, integration, and orchestration.
• Own model lifecycle management: versioning, release strategies, monitoring, drift detection, and continuous improvement.
• Design scalable, robust infrastructure patterns for AI workloads across dev/test/prod environments.
• Automate provisioning, configuration, and deployments using Infrastructure-as-Code and CI/CD practices.
• Optimise performance, reliability, and cost across compute, storage, networking, and runtime environments.
• Partner with data engineers and stakeholders to ensure data pipelines, features, and data quality meet model needs; support training, inference, and reporting using appropriate data stores.

To be successful in this role, you should meet the following requirements:

• Hands-on experience delivering AI/ML solutions into production environments.
• Strong Python skills for ML/data engineering (development, packaging, testing).
• Experience with ML frameworks such as PyTorch, TensorFlow, and/or scikit-learn.
• Experience with model serving approaches (real-time and/or batch) and building inference APIs/services.
• Solid understanding of MLOps: model registry/versioning, CI/CD for ML, reproducibility, monitoring, and drift detection.
• Strong infrastructure knowledge across servers, operating environments, databases, and platform services.
• Experience with containers and orchestration (Docker, Kubernetes) and scalable deployment patterns.
  • Experience with automation tooling (Jenkins/Git-based pipelines), Infrastructure-as-Code (Terraform/Ansible), and secrets/config management (Vault or equivalent); exposure to responsible AI and/or managed ML platforms is a plus.