SME - Azure DevOps, Terraform

Job Summary

Job Description - AI Platform Engineer Function: CSO Role: AI Platform Engineer Hiring Managers: Louise Furniss / Julie Wilson Grade: E / F Location: UK / Offshore Open Positions: 2 Target Demand: 10 Resources ________________________________________ Job Summary

• Join the CSO team to design, build, and operate enterprise-scale AI platforms that enable secure and scalable AI adoption.
• Develop platform capabilities supporting Generative AI, prompt engineering, model evaluation, and AI service delivery.
• Contribute to the implementation of Infrastructure as Code (IaC) and Security as Code practices across AI environments.
• Collaborate with security, engineering, data, and platform teams to deliver reliable and compliant AI solutions.
• Support the development of AI platform standards, governance controls, and operational best practices.
• Drive automation, scalability, and efficiency across the AI technology stack using modern DevOps methodologies.
• Enable business teams and developers to safely consume AI capabilities through robust platform engineering.

Key Responsibilities

Design, build, and maintain AI platform infrastructure supporting AI and Generative AI workloads.

• Implement Infrastructure as Code solutions using Terraform, Python, and cloud-native technologies.
• Develop and maintain automation frameworks for AI platform provisioning, deployment, and management.
• Support prompt engineering initiatives, model testing, validation, and evaluation frameworks.
• Embed Security as Code controls to ensure secure AI platform deployment and operations.
• Monitor platform health, reliability, performance, and operational metrics while driving continuous improvements.
• Collaborate with stakeholders to define platform requirements and deliver scalable enterprise AI capabilities.

Skill Requirements

Strong understanding of AI Platform Engineering, MLOps, or AI infrastructure management principles.

• Hands-on experience with Terraform and Infrastructure as Code implementation across enterprise environments.
• Proficiency in Python scripting, automation development, and platform engineering activities.
• Knowledge of prompt engineering techniques, LLM evaluation methodologies, and AI model lifecycle management.
• Experience implementing Security as Code practices, security automation, and compliance controls.
• Familiarity with cloud platforms, DevOps tooling, CI/CD pipelines, and infrastructure automation frameworks.
• Strong problem-solving, analytical thinking, stakeholder management, and troubleshooting capabilities. ________________________________________ Technical Certification Need to Have and Good to Have Need to Have
• HashiCorp Certified: Terraform Associate.
• Microsoft Certified: Azure Administrator Associate (AZ-104) or equivalent cloud administration certification.
• Python programming certification or demonstrable enterprise-level Python development experience.
• Security fundamentals certification such as CompTIA Security+ or equivalent.
• Proven experience in Infrastructure as Code, platform engineering, and automation disciplines. Good to Have
• Microsoft Certified: Azure AI Engineer Associate (AI-102).
• Microsoft Certified: Azure DevOps Engineer Expert (AZ-400).
• Certified Kubernetes Application Developer (CKAD) or Certified Kubernetes Administrator (CKA).
• Certified Information Systems Security Professional (CISSP) or Certified Cloud Security Professional (CCSP).
• MLOps, Generative AI, Prompt Engineering, or Large Language Model specialization certifications.
• Cloud provider certifications from AWS or Google Cloud related to AI, DevOps, or infrastructure.
• Certifications in Security as Code, DevSecOps, or cloud-native security practices

Other Requirements

Experience working with enterprise AI platforms, Generative AI services, or foundation model ecosystems is highly desirable.

• Exposure to AI governance, responsible AI practices, and model risk management frameworks is preferred.
• Ability to collaborate effectively across UK and Offshore teams in a global delivery environment.
• Strong communication skills with the ability to explain technical concepts to technical and business stakeholders.
• Experience supporting large-scale platform transformation, automation, and modernization initiatives.
• Passion for innovation, emerging AI technologies, and continuous learning.
• Commitment to building secure, scalable, resilient, and compliant AI platforms that deliver measurable business value.