· Lead the design and development of advanced graph data
models, graph algorithms, and graph-based machine learning solutions to unlock
complex relationship insights and enterprise value.
· Translate highly connected and complex data into actionable
business solutions using TigerGraph and graph analytics techniques within
financial services contexts.
· Architect, deploy, and operate scalable TigerGraph clusters
on AKS Kubernetes, ensuring high availability, fault tolerance, and optimal
resource utilisation.
· Drive the operationalisation of graph-based analytics and
machine learning use cases, ensuring production robustness, scalability, and
alignment with business objectives.
· Configure and manage networking, storage, and security for
graph workloads on AKS, including integration with enterprise identity, access
control, and secrets management.
· Optimise graph query
performance (GSQL), workload isolation, and system throughput across
large-scale distributed environments.
· Apply advanced graph techniques such as graph neural
networks, link prediction, community detection, and path analysis to solve
high-impact use cases.
· Build and manage enterprise knowledge graphs, enabling
advanced analytics, GenAI, and RAG capabilities grounded in
relationship-centric data.
· Enable feature
engineering and reuse through graph-derived features, enhancing downstream
machine learning models and decisioning systems.
· Deliver high-impact graph analytics solutions across fraud
detection, financial crime, customer intelligence, and network risk management.
Requirements
· Develop CI/CD pipelines for graph applications and
infrastructure using Kubernetes-native and DevOps tooling, enabling automated
deployment and monitoring.
· Provide thought leadership on graph and Kubernetes
strategy, embedding scalable graph capabilities into enterprise AI platforms.
· Continuously monitor and optimise system health, cluster
performance, cost efficiency, and model accuracy in dynamic environments.
· Evaluate emerging tools across graph, Kubernetes, and cloud
ecosystems to inform platform evolution and roadmap development.
· Communicate complex graph and infrastructure concepts
clearly to business and technical stakeholders.
· Champion experimentation and innovation in graph analytics
and distributed systems engineering.
· Support strategic initiatives, embedding graph platforms
into enterprise digital and AI transformation programmes.
Benefits
Skills Required
- Production experience with TigerGraph
- Deploying and operating TigerGraph clusters on AKS/Kubernetes
- Proficiency with GSQL and optimizing graph query performance
- Experience building graph-based ML, including graph neural networks and link prediction
- Designing and managing distributed graph infrastructure (containerization, orchestration, autoscaling)
- Implementing secure, performant data ingestion pipelines from enterprise sources (ADLS, Databricks)
- Configuring networking, storage, security, IAM, and secrets management for AKS graph workloads
- Developing CI/CD pipelines for graph applications and infrastructure using Kubernetes-native/DevOps tooling
- Experience designing and managing enterprise knowledge graphs and enabling GenAI / RAG use cases
- Mentoring teams on graph modelling, GSQL development, Kubernetes operations, and graph-based ML techniques
- Monitoring and optimising cluster health, performance, cost efficiency, and model accuracy
- TigerGraph, Kubernetes (CKA/CKAD), or cloud platform (Azure) certifications
What We Do
CyberPro Consulting (Pty) Ltd is a South African IT professional-services firm founded in 2000. It helps mid-sized and large enterprises enhance digital capabilities through enterprise, web, and mobile software, data engineering, analytics, data science, AI, cloud architecture and migration, DevOps, cybersecurity, business analysis, project management, testing, and digital transformation services. Its expertise spans banking, insurance, wealth, retail, and telecommunications clients, supporting customer journeys and user-interface design.
