The Senior ML Engineer (MLOps) owns the transition from ad-hoc ML deployments to a registered, monitored, governed ML platform — the lifecycle every data scientist and ML practitioner across the company uses. The role also curates
We are seeking an experienced Senior Data Engineer to own the pipeline-standardization and data-quality program for the enterprise lakehouse. This role ships compliance gates that block non-compliant deployments, stands up the data-quality framework, builds the dashboards
We are seeking an experienced Senior Data Architect to own the foundations every other data-platform role depends on: Infrastructure-as-Code (Terraform), CI / CD for data and ML, FinOps, the Change Advisory Board, and the reference architecture.
The Senior AI Engineer owns the enterprise LLM platform substrate that powers every generative-AI consumer across the organisation. This role designs, builds, and operates the LLM Gateway, the evaluation framework, and the AI best-practices playbook that
The Senior AI Engineer owns the enterprise LLM platform substrate that powers every generative-AI consumer across the organisation. This role designs, builds, and operates the LLM Gateway, the evaluation framework, and the AI best-practices playbook that
We are seeking an experienced Senior Data Architect to own the foundations every other data-platform role depends on: Infrastructure-as-Code (Terraform), CI / CD for data and ML, FinOps, the Change Advisory Board, and the reference architecture.
We are seeking an experienced Senior Data Engineer to own the pipeline-standardization and data-quality program for the enterprise lakehouse. This role ships compliance gates that block non-compliant deployments, stands up the data-quality framework, builds the dashboards
The Senior ML Engineer (MLOps) owns the transition from ad-hoc ML deployments to a registered, monitored, governed ML platform — the lifecycle every data scientist and ML practitioner across the company uses. The role also curates
The AI Engineer builds production agents end-to-end on an AI-native retail decisioning platform — prompt design, tool definitions, multi-step workflows on the agent runtime (LangGraph, CrewAI, or chosen framework), evaluation harnesses (golden sets, regression gates, multi-step
The DevOps / SRE Engineer owns the operational substrate of an AI-native retail decisioning platform — infrastructure, CI / CD, observability, cost meter, and incident response for a system that runs production agents taking real business
The ML Engineer builds the classical retail-ML cores that power the highest-stakes agents on an AI-native retail decisioning platform — demand forecasting that must beat a legacy system, replenishment and allocation models, causal-insight models for executive