Senior Software Engineer (GO)

Reference: 57555

We are seeking a highly skilled Senior Backend Engineer (Golang) to design, build, and scale cloud-native backend platforms that power enterprise AI and GenAI initiatives across a global banking environment. This role will focus on developing reusable engineering blueprints, establishing LLMOps best practices, and delivering secure, scalable microservices architectures that operate across hybrid cloud environments spanning public cloud providers and private data centres.

The successful candidate will play a key role in defining backend engineering standards, driving platform adoption across multiple business units, and enabling the safe and scalable use of Generative AI technologies within the organization.

Key Responsibilities
Backend Platform Engineering

• Design, develop, and maintain high-performance backend services using Golang within distributed and microservices-based architectures.
  
• Build enterprise-grade AI platform capabilities supporting LLMOps , model deployment, inference services, prompt management, model observability, and governance.
  
• Engineer reusable backend blueprints and reference architectures that serve as standardized patterns across the organization.
  
• Develop globally scalable systems capable of handling high throughput, low latency, and mission-critical workloads.
  

Cloud-Native & Hybrid Architecture

• Architect and implement backend services across hybrid environments spanning public cloud platforms and private data centres.
  
• Build and operate containerized workloads on Kubernetes (K8s) and OpenShift .
  
• Define deployment patterns, operational standards, and platform best practices for cloud-native applications.
  
• Collaborate with platform engineering teams to optimize scalability, resilience, and operational excellence.
  

Security & Platform Governance

• Embed security controls throughout the application lifecycle, including:
  • Application security
    
  • API security
    
  • Service-to-service communication security
    
  • CI/CD pipeline security
    
  • Infrastructure and platform security
    
• Ensure compliance with enterprise governance, risk, and security requirements.
  
• Contribute to secure AI adoption frameworks and responsible GenAI implementation practices.
  

Event-Driven & Data Engineering

• Design and implement event-driven architectures using Kafka .
  
• Develop highly available data services leveraging MongoDB and other enterprise data platforms.
  
• Optimize data flows, event processing, and backend performance for large-scale distributed systems.
  

Observability & Reliability

• Implement comprehensive observability solutions using:
  • Prometheus
    
  • OpenTelemetry
    
  • Grafana
    
• Establish monitoring, tracing, logging, alerting, and SRE best practices.
  
• Drive operational excellence through performance tuning, reliability engineering, and proactive incident prevention.