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AI Engineer – Contract
AND Digital. Architect and design scalable, resilient Azure AI Foundry environments aligned to enterprise cloud architecture and Azure Landing Zone principles .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Azure Cloud Architecture and AI/ML Platform Engineering, with a focus on designing scalable and resilient Azure AI Foundry environments. Proficient in establishing governance frameworks, implementing security standards, and optimizing AI platform performance and cost management.
Highest-signal resume keywords
Azure Cloud ArchitectureAI/ML Platform EngineeringEnterprise Security and Cloud GovernanceAzure DevOps and CI/CD ProcessesMicrosoft Certified: Azure Solutions Architect Expert
ATS Keywords
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Hard Skills
Azure AI FoundryAzure OpenAI ServiceBicepTerraformARM TemplatesModel Evaluation FrameworksZero-Trust PrinciplesCapacity PlanningCost Management FrameworksAutomated Deployment Pipelines
Soft Skills
Exceptional Communication SkillsPragmatic Delivery-Focused ApproachCollaboration with Technical Teams
Tools & Technologies
Azure DevOpsGitHub ActionsMicrosoft Entra IDVector DatabasesAI Search
Certifications & Qualifications
Microsoft Certified: Azure Solutions Architect Expert (AZ-305)Microsoft Certified: Azure AI Engineer Associate (AI-102)
Industry Keywords
Enterprise ArchitectureAI WorkloadsResource ControlsOperational ManagementAudit Logging
Tech Stack
Tools & technologiesAzureCloudTerraform
About the role
Key responsibilities & impact- Architect and design scalable, resilient Azure AI Foundry environments aligned to enterprise cloud architecture and Azure Landing Zone principles
- Integrate Azure AI Foundry with Azure OpenAI Service, model catalogues, prompt flows, AI Search, vector databases and custom AI tooling
- Define reusable architecture patterns for development, testing and production AI workloads
- Establish standards for resource structure, environments, deployment patterns, observability and operational management
- Design and deliver AI Agents and agentic workflows with AI Engineers
- Establish enterprise governance frameworks for Azure AI workloads
- Define and implement Azure Policy, RBAC, resource controls and access-management standards
- Implement content safety and responsible-AI guardrails
- Establish model and prompt evaluation frameworks
- Ensure audit logging, monitoring and traceability across AI platform components
- Design secure control-plane and data-plane Azure AI architectures
- Implement Private Endpoints, VNets, Managed Identities and Microsoft Entra ID
- Apply zero-trust principles and define identity, authentication and authorisation patterns
- Design highly available and, where required, multi-region AI deployment architectures
- Manage Azure OpenAI and AI platform capacity, API rate limits, quotas and Provisioned Throughput Units
- Establish performance monitoring, capacity planning, scaling, disaster recovery and business continuity strategies
- Establish cost-management frameworks, chargeback/showback models, resource tagging and cost allocation
- Monitor and optimise token usage, model utilisation and AI platform expenditure
- Design automated deployment pipelines and CI/CD processes using Azure DevOps and/or GitHub Actions
- Automate infrastructure provisioning with Bicep, Terraform or ARM templates
- Automate prompt-flow evaluation, model deployment, testing and release management
- Establish platform observability for availability, performance, usage, cost and AI workload health
- Travel 2–3 days a week to the client site in Southampton
Requirements
What you’ll need- 5+ years' experience in Azure cloud architecture, engineering or platform engineering
- 1–2+ years' experience specifically focused on enterprise AI/ML platform engineering
- Proven experience working on large-scale or enterprise Azure environments
- Strong track record of translating business and technical requirements into enterprise architecture
- Experience collaborating with AI Engineers, Cloud Engineers, Security, DevOps and Architecture teams
- Exceptional Azure architecture and technical leadership skills
- Strong understanding of enterprise security and cloud governance
- Hands-on engineering capability alongside strategic architectural thinking
- Strong understanding of AI platform scalability, reliability and cost optimisation
- Ability to establish technical standards, patterns and governance frameworks
- Excellent communication skills with technical and non-technical stakeholders
- Pragmatic, delivery-focused approach to enterprise AI adoption
- Financial experience is preferred but not required
- Microsoft Certified: Azure Solutions Architect Expert (AZ-305) certification advantageous, not required
- Microsoft Certified: Azure AI Engineer Associate (AI-102) certification advantageous, not required
Benefits
Comp & perks- 25 days bookable holiday + flexible Bank Holidays
- Pension: 6% of salary paid by AND Digital with a further 2% paid by you (can be increased by choice)
- Aviva healthcare cover (including pre-existing condition cover) for you
- Flexibenefit: £1000 assigned via the benefits portal to select or upgrade benefits; unused allowance can be taken as cash
- Life Assurance
- Income Protection
- Eye test + first pair of glasses
- Enhanced Maternity and Enhanced Partner (Paternity) Leave
- Inclusive environment and application/interview adjustment support