AI Specialist - Deployment

The AI Specialist - Deployment leads agent development, deployment, operationalisation, and lifecycle management of AI solutions on the HKBN AI+ platform in enterprise production environments. This role owns the critical bridge between AI architecture and live operations — ensuring AI agents, token services, and inference pipelines are deployed reliably, monitored effectively, and continuously optimised. This is a hands-on technical leadership role combining agent development, MLOps, infrastructure engineering, and delivery management within the HKBN Enterprise Solutions context. The AI Deploy Lead must also be familiar with real-life business processes across our clients' industries to design practical, workflow-aligned AI solutions.

About your role:

AI Deployment, Agent Development & Platform Operations

●        Design and manage inference infrastructure including GPU cluster orchestration (Kubernetes), API serving (vLLM, TGI, Triton), and load-balancing strategies on HKBN infrastructure.

●        Implement monitoring, alerting, and observability for AI production systems — covering model latency, throughput, token usage, drift detection, and cost tracking across HKBN AI+ deployments.

Delivery Leadership

●        Lead AI deployment projects from architecture handover through go-live, managing timelines, risks, and client communications.

●        Coordinate with AI Architects, Data Engineers, Security, and Infrastructure teams to resolve deployment blockers.

Cross-Tower Collaboration & Pre-Sales Support

●        Support PreSales and solutioning teams with deployment effort estimation, infrastructure sizing, and operational cost modelling for multi-tower opportunities.

●        Contribute to the HKBN AI+ platform evolution by feeding back operational insights, performance data, and client requirements.

About you:

●        Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent practical experience).

●        4+ years in DevOps, Agent development, platform engineering, or production infrastructure roles, with at least 2 years focused on AI/ML deployment.

●        Strong hands-on experience with Kubernetes — including GPU scheduling, node pools, and resource optimisation.

●        Experience deploying and serving LLMs in production using vLLM, TGI, Ollama, or similar inference engines.

●        Solid understanding of CI/CD pipelines for ML models (MLflow, Kubeflow, Argo Workflows, or equivalent).

●        Experience with monitoring and observability stacks (Prometheus, Grafana, OpenTelemetry).

●        Strong scripting and automation skills in Python and Bash.

●        Experience deploying AI in regulated or security-conscious enterprise environments.

●        Cloud certifications (AWS Solutions Architect, GCP Professional, Azure AI).