SA, Network System AI Engineer, Group Infrastructure & Cloud, Group Technology

Business Function
Group Technology enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group Technology, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels.

Responsibilities

• Design, develop, and deploy AI-enabled applications and automation solutions for network operations and infrastructure management.

• Build web applications, dashboards, and self-service portals using Python and React.js.

• Develop and integrate AI solutions leveraging LLMs, RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), AI agents, and vector databases.

• Create automation workflows for network provisioning, monitoring, anomaly detection, predictive maintenance, and operational efficiency.

• Develop, test, troubleshoot, and maintain applications, scripts, and APIs across Windows and Linux environments.

• Integrate applications with internal and external systems through REST APIs and other interfaces.

• Collaborate with network engineering teams to translate business requirements into technical solutions.

• Ensure solutions meet security, compliance, risk management, and operational standards.

• Maintain technical documentation, code quality, and development best practices.

• Provide support, enhancements, and troubleshooting for existing applications and platforms.

• Participate in on-call support and incident resolution as required.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.

• Strong hands-on development experience in Python and React.js.

• Proven experience building web applications, APIs, automation tools, and backend services.

• Experience designing and implementing RAG, MCP, AI agents, and LLM-powered applications.

• Knowledge of AI frameworks, prompt engineering, vector databases.

• Experience integrating AI solutions with enterprise systems and network platforms.

• Familiarity with DevOps/MLOps practices, CI/CD pipelines, containerization, and deployment automation.

• Strong analytical, troubleshooting, and problem-solving skills.

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