Lead Data & AI Platform Engineer

Job summary

The Lead Data & AI Platform Engineer is tasked with designing, building, and operating platforms that facilitate data engineering and AI delivery. This role involves leading the creation of secure cloud infrastructure, establishing operational practices for AI solutions, and ensuring observability across data pipelines and AI applications using technologies such as Azure, AWS, and Terraform.

Qualifications

• 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

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

Skills

Relocation