Lead Data & AI Platform Engineer

We are seeking aLead Data & AI Platform Engineer to design, build, and operate the platforms that support data engineering and AI delivery across a range of client engagements. You will lead platform automation, deployment, governance, observability, and reliability for data pipelines, machine learning systems, LLM applications, and AI agents.

This is a hands-on technical leadership role. You will guide architectural decisions, establish reusable engineering practices, and work closely with data and AI teams to bring solutions into production.

Responsibilities

• Lead the design and implementation of secure, scalable cloud infrastructure for data and AI workloads
• Build reusable infrastructure and CI/CD patterns for data platforms, applications, models, and AI agents
• Establish operational practices for AI solutions, including deployment, versioning, evaluation, monitoring, and rollback
• Implement observability across pipelines and AI applications, including logs, metrics, traces, alerts, quality measures, and cost monitoring
• Improve platform reliability through automation, incident response, performance tuning, and capacity planning
• Define standards for cloud security, identity and access management, secrets, networking, and governance
• Support teams deploying LLM applications and agentic systems, including their model integrations, tool calls, and external APIs
• Use AI-assisted tools to improve infrastructure development, troubleshooting, and operational workflows, while validating their output
• Partner with architects, engineers, and stakeholders to make platform decisions and explain technical trade-offs
• Mentor engineers and contribute to technical standards, reusable templates, and platform roadmaps

Requirements

• Strong hands-on experience in platform engineering, DevOps, site reliability engineering, or MLOps, with experience leading technical delivery
• Experience with at least one major cloud platform: Azure, AWS, or Google Cloud
• Strong infrastructure as code skills, such as Terraform
• Experience designing CI/CD pipelines and automated deployment processes
• Scripting or programming experience, preferably in Python
• Experience operating data platforms, distributed workloads, or cloud-native applications
• Strong understanding of monitoring, logging, alerting, incident response, and production troubleshooting
• Knowledge of cloud networking, identity and access management, secrets management, and security practices
• Practical understanding of AI/ML platform operations, including model deployment, versioning, monitoring, and lifecycle management
• Understanding of the operational needs of LLM applications and AI agents, including tracing, evaluation, latency, reliability, and cost
• Ability to lead technical decisions, mentor engineers, and collaborate directly with client and delivery teams

Nice to have

• Experience with Databricks, Snowflake, Microsoft Fabric, or similar data and AI platforms
• Experience with MLflow, model serving platforms, or model registries
• Experience deploying and observing RAG applications or agentic systems
• Familiarity with LLM evaluation, guardrails, and monitoring for response quality
• Experience with Kubernetes, containers, API gateways, or service orchestration
• Experience applying AI to operations, such as alert correlation, incident triage, or root cause analysis
• Experience with GitHub Actions, Azure DevOps, GitLab CI, or similar tools
• Experience with Databricks Asset Bundles, Unity Catalog, or equivalent capabilities
• FinOps experience, including workload optimisation and cloud cost attribution
• Consulting experience, including platform assessments, solution design, and technical estimation