AI Platform & LLMOps Expert (Principal / Lead)

This role is for an international FinTech & Telecom group building a world-class AI capability. The position involves building, operating, and maintaining AI platforms that support AI agents, models, and applications for next-generation financial services across multiple markets.

• Minimum 8–10 years in software, platform, cloud, or Site Reliability Engineering (SRE).
• 2–3 years leading or guiding engineering teams.
• Hands-on experience building and running enterprise-grade cloud platforms, Infrastructure as Code (IaC), containers, and automated pipelines.
• Practical experience with LLMOps and MLOps, focusing on model evaluation, monitoring, tracing, and cost management.
• Strong proficiency with cloud platforms (AWS, Azure, GCP), Kubernetes, Infrastructure as Code tools (Terraform, Ansible), and secrets management.
• Experience with on-call shifts, incident response, and root-cause analysis in high-availability environments.
• Exposure to regulated sectors requiring formal change management, audit, and security.

Nice to have:

• Recognized cloud, platform, or SRE certifications (e.g., AWS, Azure DevOps, Solutions Architect, CKA, TOGAF).
• Postgraduate qualification (Master's degree) in a technical field.
• Experience in FinTech, banking, or other high-volume transactional platforms.

AI Platform & Release Mechanics:

• Build and maintain multi-environment AI platform infrastructure, CI/CD pipelines, container orchestration, and release mechanics.

Model Operations & LLMOps:

• Manage production model lifecycle, including provisioning, dynamic routing, versioning, fallback strategies, latency optimization, and cost control.

Evaluation & Quality Gates:

• Build and own evaluation harnesses, regression test suites, and pre-release quality gates to ensure model and agent safety and performance.

Observability & Incident Leadership:

• Design the full observability stack including monitoring, tracing, alerting.
• Hold production accountability including on-call shifts, incident response leadership, and root-cause analysis.

Application Interfaces & APIs:

• Deliver full-stack applications, developer interfaces, and robust APIs for AI service consumption.