Deeplight AI
Technology
DevOpsEngineer
Neural analysis suggests this role is
optimal for Mid-level candidates.
“DevOps Engineer at Deeplight AI. Skills: Infrastructure-as-code, Kubernetes, AKS, Azure DevOps. Govern AWA Azure infrastructure. Manage AKS clusters”
Industry & Context.
Troubleshooting; Root cause analysis
What They're Looking For.
Must Have
5+ years DevOps/SRE/Platform Engineering, 2+ years Azure ecosystem focus, Production Kubernetes deployments, Bachelor's degree in Computer Science, Bachelor's degree in Systems Engineering
Nice to Have
Kubernetes Workload Identity proficiency, Managed identity architectures proficiency, Azure Key Vault access security profiles proficiency, Azure AI Foundry familiarity, API Management platforms familiarity, Azure Event Hubs familiarity, Kafka consumer groups familiarity, ADLS Gen2 storage structure management familiarity, Azure Administrator Associate (AZ-104), Azure DevOps Engineer Expert (AZ-400), Certified Kubernetes Administrator (CKA)
What You'll Do.
Govern AWA Azure infrastructure
Manage ADLS Gen2 accounts
Manage API Management configurations
Manage private endpoints
Manage Key Vault instances
Design automated Azure DevOps pipelines
Manage container compilation
Manage Notary v2 image signing
Manage infrastructure deployments
Manage validation testing gates
Enforce network policies
Enforce pod isolation
Manage workload identities
Manage KEDA autoscaling rules
Oversee container registries
Enforce image signing
Monitor vulnerability tracking outputs
Maintain admission control policies
Administer access architectures
Manage managed identity configurations
Manage automated TLS lifecycles
Manage cryptographic secret rotation
Construct KQL queries
Construct alerting conditions
Track runtime failures
Track token utilization
Implement platform security
Manage private connectivity endpoints
Manage Azure Policy enforcement
Manage enterprise firewall architectures
Define automated disaster recovery
Implement automated disaster recovery
Validate automated disaster recovery
How You'll Work.
Team & Collaboration
AI Centre of Excellence
Full Job Description
DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations. At DeepLight, we don't believe in "off-the-shelf" fixes. We deliver tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, ensuring that innovation is both scalable and secure. From building robust data foundations to deploying sophisticated AI platforms, we empower our clients to lead in an increasingly automated world. The DevOps Engineer owns the Agentic Workflow Automation (AWA) platform's deployment architecture, infrastructure-as-code (IaC), CI/CD pipelines, and continuous operational reliability. Operating within the AI Centre of Excellence (AICoE) at a Mid-level capacity, this position serves as the primary guardian of the cloud-native infrastructure within the bank's Azure UAE environment. The role ensures that every critical platform component—ranging from AKS namespaces and KEDA autoscalers to ADLS Gen2 storage lifecycles and firewall configurations—is entirely automated, secure, and reproducible strictly from code, eliminating manual interventions. ### Your responsibilities as the DevOps Engineer include: * Maintaining and governing all AWA Azure infrastructure utilizing Terraform or Bicep, covering multi-namespace AKS clusters, ADLS Gen2 accounts with WORM policies, API Management configurations, private endpoints, and Key Vault instances. * Designing and optimising automated Azure DevOps pipelines managing the full lifecycle from container compilation, ACR pushing, and Notary v2 image signing, through to managed infrastructure deployments and validation testing gates. * Managing multi-namespace AKS clusters, enfo
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