Golang Engineer - AI

Cisco Systems, a leading US technology company, is seeking a Golang Engineer - AI to design, build, and deploy high-performance microservices and scalable backend systems. The role focuses on developing production-grade distributed systems using Golang, while contributing to the integration of AI-powered capabilities within modern applications.This is a fully remote role from Egypt, involves close collaboration with US-based teams to build reliable, scalable, and secure backend services deployed across cloud environments.

In this role, you will design, build and maintain scalable distributed microservices using Golang, ensuring performance, reliability, and operational excellence. You will also collaborate with AI teams to integrate intelligent services and support AI-driven features such as retrieval systems, agent workflows and model-powered APIs within modern backend architectures.

Job Description

• Design, develop, and maintain high-performance microservices using Golang, building scalable backend systems that support modern applications and intelligent services.
• Architect and implement RESTful and gRPC APIs to enable reliable communication between distributed services and internal platforms.
• Build and optimize data pipelines and backend services that support AI-powered features such as retrieval systems, inference services, and intelligent automation.
• Develop and integrate Retrieval-Augmented Generation (RAG) pipelines, vector search, or knowledge-based retrieval systems when required for AI-powered applications.
• Collaborate with AI/ML teams to integrate model inference services, embeddings, or AI-driven APIs into scalable Golang microservices.

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• Design event-driven architectures using messaging systems such as Kafka, RabbitMQ, or similar technologies to support asynchronous processing and distributed workflows.
• Implement scalable data models and storage solutions using SQL and NoSQL databases such as PostgreSQL, MongoDB, or similar systems.
• Ensure performance, reliability, security, and observability across backend services through monitoring, logging, and automated testing.
• Deploy and manage services using containerized environments (Docker) and orchestration platforms such as Kubernetes.
• Integrate backend services with cloud infrastructure platforms such as AWS, GCP, or Azure, ensuring scalability and operational stability.
• Contribute to the implementation of AI system monitoring, evaluation pipelines, and guardrails to maintain quality and reliability in production environments.
• Work closely with cross-functional teams to continuously improve system architecture, scalability, and service performance.

Qualifications

• 2+ years of experience developing scalable backend systems and microservices using Golang.

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• Proven experience designing and building scalable microservices architectures in distributed environments.
• Strong proficiency in building RESTful and gRPC-based services, with a solid understanding of API design, WebSockets, and API security best practices.
• Experience working with containerization technologies such as Docker and orchestration platforms like Kubernetes.
• Hands-on experience with CI/CD pipelines and modern DevOps practices for automated testing, integration, and deployment.
• Familiarity with cloud environments such as AWS, GCP, or Azure, including deploying and managing backend services in cloud infrastructure.
• Experience working with relational and non-relational databases (e.g., PostgreSQL, MongoDB, or similar technologies).
• Understanding of asynchronous and event-driven architectures, using messaging systems such as Kafka, RabbitMQ, or similar technologies.
• Experience with front-end technologies such as React.js, Vue.js, or Angular to collaborate effectively with UI teams and integrate backend services with user-facing applications.
• Strong understanding of system performance, scalability, reliability, and security in production environments.
• Exposure to AI-powered applications or intelligent services, with experience in RAG systems, agent workflows, model optimization, or AI observability.