Infrastructure Engineer – Conversational AI Platforms (Contract) GautengHybrid ISB1401582

Expert Infrastructure Engineer Conversational AI Platforms (Contract)

Our client is seeking an elite AI infrastructure engineer who designs and deploys production-grade runtime environments and platform architectures that power conversational AI systems and automate enterprise workflows at scale!

Architect sophisticated secure and cost-efficient cloud environments using Azure Kubernetes (AKS) Helm and Infrastructure-as-Code to support large-scale conversational AI and agentic platforms!

The ideal candidate is an industry-leading platform expert with a proven track record operating mission-critical enterprise infrastructure who excels at container orchestration establishes robust CI/CD and observability frameworks tailored for LLM workloads bridges the gap between development and operations and mentors engineering teams on DevOps maturity and cloud compliance!

Expert cloud infrastructure engineering with Azure and production Kubernetes (AKS)

Hybrid and remote working flexibility with 1960 flexible annual hours

Platform leadership role driving automation security-by-design and LLMOps

• POSITION: Contract: 01 August 2026 31 December 2028
• EXPERIENCE: 8 years related experience
• COMMENCEMENT: 01 August 2026
• LOCATION: Hybrid: Midrand/Menlyn/Rosslyn/Home Office rotation
• TEAM: DevOps / Conversational AI & Agentic Systems Platform

Qualifications / Experience

• Degree in Computer Science Information Technology Engineering or comparable practical experience
• 5 years of professional experience in infrastructure platform engineering or DevOps roles
• Proven track record operating mission-critical platforms in an enterprise environment
• Hands-on experience with cloud-native architectures and Kubernetes in production
• Practical exposure to AI/ML platform support is required; conversational AI experience is a strong plus
• Experience working in cross-functional international teams
• Strong problem-solving mindset with the ability to balance speed stability and compliance

Level Criteria

• Communication: Negotiate (discussions and compromise. Issues are short-term operational medium-term tactical or limited strategic nature)
• Delivery: Outcomes are complex and require the integration of several nuanced systems and processes in order to deliver on the required standards. Employee may be expected to provide guidance to lower level employees
• Knowledge: Industry Leader - represents the best practice leader for a product or multiple products in a region or country and will typically represent the product or service in professional boards
• Problem Solving: Create a product or system based on international best practice or guidelines from other companies that have implemented the same or similar solutions. The problems are complex and may require complex solutions in single systems
• Supervision: Can solve escalated tasks that require a deep understanding of the product or service for which there are no senior level authority to defer the task to. Can lead team leaders who each have their own team members

Essential Skills Requirements

• Cloud infrastructure engineering (Azure preferred) with a focus on high-availability scalable AI platforms (Kubernetes container orchestration networking IAM)
• Strong hands-on experience with Kubernetes (AKS) Helm and platform-level CI/CD pipelines
• Solid understanding of conversational AI architectures (LLM-based services APIs grounding layers vector stores)
• Infrastructure-as-Code expertise (Terraform ARM/Bicep) for reproducible and compliant environments
• Security-by-design mindset: identity secrets management network isolation and secure service communication
• Observability fundamentals: logging metrics tracing for AI workloads (latency token usage cost drivers)
• Strong collaboration skills with Dev Data Science and Product to translate functional requirements into resilient infrastructure

Advantageous Skills Requirements

• Experience operating enterprise-grade AI platforms under regulatory data protection and compliance constraints
• Knowledge of cost optimization for AI workloads (GPU/CPU trade-offs scaling strategies usage-based charging)
• Exposure to MLOps / LLMOps concepts (model deployment versioning prompt lifecycle evaluation)
• Familiarity with event-driven architectures (Kafka Azure Event Hub) in AI-driven systems
• Experience with cross-region / multi-environment setups (DEV INT PREPROD PROD)
• Understanding of internal enterprise IT standards security policies and approval processes
• Ability to coach engineers and shape platform engineering best practices

Role Requirements

• Own the end-to-end infrastructure landscape for Conversational AI platforms (e.g. ConvAIS)
• Design implement and operate secure scalable and cost-efficient AI runtime environments
• Act as the technical backbone between product development data science and operations
• Define infrastructure standards reference architectures and guardrails for conversational AI use cases
• Ensure platform reliability performance and availability including incident support and root cause analysis
• Enable fast but compliant onboarding of new AI use cases and teams
• Drive automation first: CI/CD environment provisioning monitoring and recovery
• Contribute to platform roadmap discussions with a strong infrastructure and operational perspective
• Act as a multiplier: mentoring engineers and spreading infrastructure and DevOps maturity

Please Note: South African citizens/residents preferred.

Valid work permit holders will be considered.

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• If you do not receive a response within 2 weeks please consider your application unsuccessful.

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