Senior Software Engineer (GO)
Source Group International
Reference: 57555We 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.
Not sure what skills you will need for this opportunity Simply read the full description below to get a complete picture of candidate requirements.
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 securityAPI securityService-to-service communication securityCI/CD pipeline securityInfrastructure and platform securityEnsure 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:PrometheusOpenTelemetryGrafanaEstablish monitoring, tracing, logging, alerting, and SRE best practices. xrnqpay Drive operational excellence through performance tuning, reliability engineering, and proactive incident prevention.
Not sure what skills you will need for this opportunity Simply read the full description below to get a complete picture of candidate requirements.
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 securityAPI securityService-to-service communication securityCI/CD pipeline securityInfrastructure and platform securityEnsure 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:PrometheusOpenTelemetryGrafanaEstablish monitoring, tracing, logging, alerting, and SRE best practices. xrnqpay Drive operational excellence through performance tuning, reliability engineering, and proactive incident prevention.
Reference: WJ-799_34372590