Golang Developer

Accountabilities:: Design, build, and maintain scalable data pipelines and platform infrastructure supporting data ingestion, processing, and distribution. Develop and maintain backend services integrated with AI Agent systems and production AI/LLM workflows. Build, manage, and monitor Agent workflows and related infrastructure to ensure reliable production performance. Develop monitoring, alerting, and observability capabilities covering data quality, pipeline stability, and AI system health. Collaborate with AI, product, frontend, DevOps, and QA teams to align data infrastructure with platform and AI Agent requirements. Support and maintain existing backend services, including B9, ensuring operational stability and continuity during team transitions. Identify and resolve infrastructure, pipeline, and backend issues while contributing to continuous improvements in reliability and scalability. Help establish robust engineering practices for monitoring, troubleshooting, and maintaining AI-enabled backend systems. Requirements: 3–6 years of backend development experience, with Golang as the primary technology and recent hands-on production experience. Proven experience building data pipelines, data platforms, or large-scale data processing systems. Experience with AI monitoring, observability tools, or Agent engineering, with the ability to integrate AI and LLM workflows into production backend systems. Strong understanding of distributed systems and microservice architectures. Practical experience with relational and NoSQL databases and message queue technologies such as Kafka. Familiarity with AI Agent frameworks, LLM integration, or related AI tooling and development practices is a plus. Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, product-focused environment. Bachelor's degree or higher in Computer Science, Engineering, or a related technical field. Benefits: Work-from-home arrangement, with the specific setup varying according to business team and role requirements. Competitive salary and company benefits. Opportunity to work on AI Agent systems, LLM integrations, data platforms, and scalable backend infrastructure. Exposure to distributed systems, microservices, observability, message queues, and modern AI tooling. Collaboration with cross-functional AI, product, engineering, DevOps, and QA teams. Fast-paced, innovative environment with opportunities for autonomy and professional growth. Continuous learning and career development opportunities. Opportunity to contribute to high-scale technology products and production systems.