SC Cleared Principle Devops Engneer - AI, Azure And AWS

fortice; United States; Remote; GBP 100,000 - 160,000; Full time

Job summary

Fortice Ltd is seeking a Principle DevOps role focused on designing, building and optimising an enterprise AI Platform across cloud environments. The candidate will provide technical foundations, tooling, automation and governance to accelerate AI adoption with emphasis on security, resilience and cost-effective delivery.

The role requires experience with Azure/AWS, IaC, MLOps, and strong platform engineering capabilities, while ensuring alignment with governance standards across the

Qualifications

• Design, build and operate enterprise AI platforms with cloud-native infrastructure.
• Develop and manage AI landing zones, development environments and experimentation platforms.
• Implement IaC, automation and self-service capabilities across environments.
• Build and maintain CI/CD and MLOps pipelines for AI product delivery.
• Enable secure integration of AI services, APIs, agents, models and orchestration frameworks.

Responsibilities

• Design, build and maintain enterprise AI Platform capabilities across cloud environments.
• Develop and manage AI landing zones, development environments and experimentation platforms.
• Implement Infrastructure-as-Code, platform automation and self-service engineering capabilities.
• Build and maintain CI/CD and MLOps pipelines supporting AI solution delivery.
• Enable secure integration of AI services, APIs, agents, models and orchestration frameworks.
• Implement platform observability, monitoring, logging and operational support capabilities.
• Establish security controls, governance policies and operational guardrails for AI services.
• Support deployment, scaling and operational management of AI products and AI-powered services.
• Evaluate emerging AI tooling, foundation model platforms and supporting technologies.
• Optimise platform performance, resilience, security and cloud consumption costs.
• Develop reusable platform services, accelerators, templates and reference architectures.
• Provide technical leadership and guidance to engineering, data and AI delivery teams.
• Ensure alignment with enterprise architecture, security, platform and AI governance standards.
• Contribute to the organisation's AI capability through a hub-and-spoke operating model.

Skills

Platform engineering

Cloud infrastructure

AI platforms

DevOps

CI/CD

MLOps

Automation

Tools

Terraform

Bicep

CloudFormation

Docker

Kubernetes

Azure

AWS

Job description

Principle DevOps

Clearance required: BPSS + SC

This role requires additional vetting, which means this could take longer than our normal onboarding process. You will require additional vetting for this position, which means the process can take longer than the usual onboarding process with Capgemini. Please do not hesitate to get in touch if you have any queries.'

Interview process: Tech IV

Location: Remote

Sector: Public

End User: Client

IR35 Status: PAYE via Umbrella company only

Job Description:

Role Summary

• Design, build and optimise the enterprise AI Platform that enables the development, deployment and operation of AI products, solutions and services.
• The role provides the technical foundations, tooling, automation and governance required to accelerate AI adoption while ensuring security, resilience, scalability and cost-effective delivery across the organisation.

Key Responsibilities

• Design, build and maintain enterprise AI Platform capabilities across cloud environments.
• Develop and manage AI landing zones, development environments and experimentation platforms.
• Implement Infrastructure-as-Code, platform automation and self-service engineering capabilities.
• Build and maintain CI/CD and MLOps pipelines supporting AI solution delivery.
• Enable secure integration of AI services, APIs, agents, models and orchestration frameworks.
• Implement platform observability, monitoring, logging and operational support capabilities.
• Establish security controls, governance policies and operational guardrails for AI services.
• Support deployment, scaling and operational management of AI products and AI-powered services.
• Evaluate emerging AI tooling, foundation model platforms and supporting technologies.
• Optimise platform performance, resilience, security and cloud consumption costs.
• Develop reusable platform services, accelerators, templates and reference architectures.
• Provide technical leadership and guidance to engineering, data and AI delivery teams.
• Ensure alignment with enterprise architecture, security, platform and AI governance standards.
• Contribute to the development of the organisation's AI capability through a hub-and-spoke operating model.

Required Technical Competencies

• Strong platform engineering, cloud infrastructure and software engineering expertise.
• Experience building and operating AI platforms in Microsoft Azure and AWS.
• Experience with Azure AI Foundry, AWS Bedrock and associated AI ecosystem services.
• MLOps, DevOps and CI/CD practices supporting AI solution delivery.
• Infrastructure-as-Code technologies such as Terraform, Bicep or CloudFormation.
• Containerisation and orchestration technologies including Docker and Kubernetes.
• API management, integration architectures and event-driven platforms.
• Platform observability, monitoring, logging and operational support tooling.
• Identity, security, governance and compliance controls within cloud environments.
• Experience supporting AI agents, orchestration frameworks, retrieval architectures and model integration patterns.
• Cost optimisation, FinOps and cloud consumption management.
• Automation and Scripting technologies supporting platform operations.

Aptitudes/Personal Attributes

• Strong technical curiosity and passion for emerging AI technologies.
• Strategic mindset with the ability to translate business needs into scalable platform capabilities.
• Pragmatic approach to balancing innovation, risk, security and cost.
• Passion for automation, standardisation and engineering excellence.
• Adaptable and responsive to rapidly evolving AI technologies and market developments.
• Collaborative and supportive team player capable of working across multidisciplinary teams.
• Strong ownership, accountability and delivery focus.
• Excellent communication skills with the ability to explain complex technical concepts clearly.
• Comfortable operating in ambiguity and shaping emerging capabilities.
• Committed to continuous improvement and knowledge sharing.