Senior System Engineer

Responsibilities:

• Design, architect, and maintain scalable distributed systems and infrastructure for our Vision AI platform.
• Lead the design and implementation of high-performance, fault-tolerant systems using Go, MongoDB, and modern cloud technologies.
• Architect and optimise system infrastructure for handling large-scale video processing, ML inference pipelines, and real-time data streams.
• Design and implement monitoring, observability, and alerting systems to ensure system reliability and performance.
• Lead infrastructure automation, CI/CD pipelines, and infrastructure-as-code initiatives.
• Collaborate with ML engineers to optimise model deployment infrastructure and inference pipelines.
• Design and implement disaster recovery, backup, and high-availability solutions.
• Mentor junior engineers and establish best practices for system design, reliability, and scalability.
• Troubleshoot complex system issues, perform root cause analysis, and implement preventive measures.
• Stay current with cloud infrastructure trends, containerization technologies, and distributed systems best practices.

Requirements:

• 3+ years of proven experience as a System Engineer, DevOps Engineer, or Site Reliability Engineer, with expertise in building and maintaining large-scale distributed systems.
• Experience with Go (our backend language) or another systems language, and with MongoDB or other NoSQL databases.
• Strong experience with cloud platforms (AWS, GCP, Azure), including compute, storage, networking, and managed services.
• Expert-level knowledge of containerization (Docker, Kubernetes) and orchestration platforms.
• Experience designing and implementing CI/CD pipelines, infrastructure-as-code (Terraform, CloudFormation), and automation tools.
• Deep understanding of distributed systems, microservices architecture, and system design principles.
• Strong experience with monitoring and observability tools (Prometheus, Grafana, Datadog, etc. ).
• Expertise in Linux systems, networking, security, and performance optimisation.
• Experience with video streaming, real-time data processing, or ML infrastructure is highly preferred.
• Strong problem-solving skills, systems thinking, and ability to work under pressure.
• Excellent communication skills and ability to lead technical discussions and mentor team members.
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience.

Skills

AWS, Azure, Docker, GCP, Go, Kubernetes