Staff Platform Engineer

Job summary

Shapes and evolves secure, scalable platform capabilities for teams to build, deploy, and operate AI/ML workloads across the model lifecycle. This hands-on Staff-level role leads MLOps, reusable automation, production reliability, and FinOps, using cloud-native engineering, Kubernetes, containers, and infrastructure as code to improve developer experience while balancing security, performance, resilience, and cost.

Qualifications

• Strong software engineering skills, including Python or another relevant language, API development, automated testing, and maintainable tooling.
• Deep understanding of cloud-native engineering, containers, Kubernetes, infrastructure as code, and automated delivery.
• Practical experience taking AI/ML workloads into production, including model pipelines, artefact and version management, deployment, serving, and monitoring.
• Understanding of AI/ML workload operations, including reproducibility, data and model dependencies, compute requirements, and production performance.
• Experience with reliability engineering practices, including service-level objectives, observability, capacity planning, incident response, and recovery.
• Demonstrated ability to automate recurring manual work and improve developer and operator experience.
• Experience with FinOps principles, including cost allocation, consumption visibility, rightsizing, and workload optimisation.
• Experience embedding security, access controls, and operational governance in engineering workflows.
• Strong technical judgement and ability to influence across teams, mentor engineers, and deliver measurable improvements.

Responsibilities

• Build and evolve AI/ML platform capabilities for model training, evaluation, deployment, serving, and monitoring.
• Embed versioning, traceability, automated checks, controlled promotion, and rollback in AI/ML delivery workflows.
• Develop reusable infrastructure, deployment patterns, and operational tools for self-service adoption.
• Use incidents, performance trends, and support issues to address root causes and prevent recurring failures.
• Improve cost visibility, ownership, workload scheduling, scaling, resource utilisation, and capacity management.
• Embed security and operational controls in platform design and align teams around reusable solutions.

Skills

Industry

Relocation