1. Role Purpose
The Automation Manager is responsible for designing, implementing, and managing automation capabilities across network and datacenter infrastructure domains, with a focus on execution, integration, monitoring, and operational efficiency.
The role will enable StarHub's transformation towards automation-first operations, AI-enabled infrastructure management, and optimized data center utilization, including energy and space optimization.
2. Key Responsibilities
a) IP & Broadband(Core + Access + Transmission)
- Design and implement automation frameworks across:
1. IP Core (BNG, routing)
2. Broadband Access (OLT/ONT)
3. Transmission and transport networks - Enable automated provisioning, configuration management, and lifecycle operations.
- Develop standard APIs and integration interfaces for network actions.
- Implement configuration compliance and drift management mechanisms.
- Support high availability and resilience readiness (failover, rerouting support).
- Integrate network telemetry into centralized platforms AI-driven diagnostics and closed-loop automation workflows.
- Ensure all automation workflows are secure, auditable,and compliant.
b) Data Centre Operations (Infrastructure Automation + Energy & Space Optimization)
Infrastructure Automation
- Automate compute, storage, and network provisioning across data center environments.
- Develop runbook automation for operational tasks (restart, failover, scaling).
- Automate patching, upgrades, and lifecycle management.
- Enable infrastructure data pipelines and integrations to support AI-based anomaly detection and predictive maintenance systems.
- Enable event-driven execution workflows from monitoring systems.
- Maintain automation pipelines (CI/CD) for infrastructure operations.
- Ensure robust execution frameworks with rollback and validation mechanisms.
Energy & Space Optimization
- Enable centralized monitoring of:
1. Power consumption (UPS, PDU)
2. Cooling systems (HVAC, CRAC)
3. Environmental metrics (temperature, airflow, humidity) - Support visibility into:
1. Rack utilization, whitespace, and capacity headroom - Enable automation readiness for:
1. Cooling optimization and airflow balancing
2. Power utilization tracking (PUE and efficiency metrics) - Support capacity planning across space, power, cooling, and network layers.
- Enable execution of optimization actions to improve energy efficiency and reduce costs.
- Support data collection and execution readiness for AI-driven energy optimization (cooling efficiency, power balancing).
- Provide data support for sustainability and energy reporting initiatives.
c) Business Innovation& Strategic Projects
- Embed automation-first principles intotransformation programs (e.g., iBNG, SiX AntiDDoS, IP-Optical SRv6 Network etc).
- Enable zero-touch provisioning (ZTP) for new deployments.
- Develop API-driven and programmable interfaces for new systems.
- Standardize integration patterns across legacy and next-generation platforms.
- Support end-to-end lifecycle automation (deploy, upgrade, decommission).
- Ensure all new platforms are automation-ready from Day 1.
- Provide execution-layer support to orchestration systems (without owning orchestration logic).
d) Monitoring, Visibility & Dashboard Enablement
- Implement centralized monitoringframeworks across network and data center domains.
- Enable real-time visibility of performance, utilization, and environmental metrics.
- Integrate telemetry into DCIM and monitoring platforms.
- Support development of:
1. Operational dashboards (NOC / CXOps)
2. Executive dashboards (capacity, utilization, risk) - Enable alarm ingestion and visualization (without owning RCA logic).
- Ensure data consistency and accuracy for reporting and governance.
- Support multi-site visibility across data center environments.
- Enable dashboards that incorporate AI-driven insights (e.g., anomaly indicators, predictive alerts)
- Ensure telemetry pipelines support AI/ML consumption (real-time, structured, high-quality data feeds).
e) Automation of Operations
- Develop automation for:
1. Provisioning and configuration management
2. Infrastructure and network lifecycle operations
3. Runbook automation for repetitive tasks - Enable execution of:
1. Network actions (configuration updates, resets)
2. Infrastructure actions (restart, scaling) - Provide secure, standardized APIs for execution.
- Ensure workflows/MOPs include:
1. Validation, rollback, retry mechanisms
2. Comprehensive logging and audit trails - Maintain high reliability and performance of execution pipelines
- Ensure all actions are controlled, pre-defined, and compliant with governance policies
- Ensure all automation interfaces are API-driven and consumable by AI orchestration platforms
f) Optimization Execution Support
- Execute approved optimization actions across:
1. Network infrastructure
2. Data center systems
- Support implementation of:
1. Energy optimization initiatives (cooling, power efficiency)
2. Space optimization (rack consolidation, capacity balancing) - Ensure execution is:
1. Controlled, non-disruptive, and auditable - Support post-implementation validation and verification of outcomes
- Provide execution readiness for closed-loop automation systems (without decision ownership)
g) Cross-Domain and Cross-Functional Responsibilities
- Define and enforce automation standards, frameworks,and best practices
- Standardize API governance, data models, and integration protocols
- Ensure scalability across multi-site environments (including large-scale data center deployments)
- Maintain reliability, performance, and resilience of automation platforms
- Ensure security, auditability, and compliance of all automation workflows
- Drive improvements in automation maturity and operational efficiency
3. Qualifications & Experience
- Bachelor's Degree in Engineering, Computer Science, orrelated field
- 6-10 years of experience in
1. Network or data center operations
2. Automation / system integration roles
Technical Skills:
- Strong understanding of:
1. IP networking and broadband architecture
2. Data center infrastructure (power, cooling, monitoring) - Experience with:
1. Automation tools (Python, Ansible, Scripting
2. API integrations and system orchestration
3. Monitoring and observability platforms
4. AI/ML-enabled operations (AIOps) concepts and data pipelines
Preferred Skills:
- Exposure to:
1. DCIM tools
2. Cloud environments (AWS / GCP / Azure)
3. TR-069 / TR-369 (device management) - Familiarity with data platforms (e.g., telemetry systems, data lakes)
- Exposure to AI-driven operations platforms (AIOps / observability / closed-loop systems)
