
Solution Architect
- Perth, WA
- Contract
- Full-time
- Design and document a secure, scalable cloud architecture capable of processing 1,000+ hours of video daily from varied sources and environments.
- Define multi-tenant infrastructure, data pipelines, and security approaches for GPU-accelerated workloads with surge processing capability.
- Provide recommendations on languages, frameworks, cloud services, and toolchains for video analytics SaaS scalability.
- Oversee architecture design reviews and guide product milestones.
- Develop cloud resource management strategies and advise on monetisation models.
- Contribute to cloud migration strategies and validate infrastructure decisions.
- Define infrastructure and DevOps principles for continuous delivery and horizontal scaling.
- Implement CI/CD and MLOps workflows for media processing, including blue-green deployments and Infrastructure-as-Code.
- Establish monitoring and observability practices tailored to GPU workloads.
- Mentor engineering teams in cloud-native and scalable system practices.
- System architecture blueprint and technical stack recommendations.
- Cloud infrastructure design and cost analysis documentation.
- Security, scaling, and monitoring strategies.
- CI/CD and MLOps pipeline architecture for video analytics.
- Regular architecture review sessions and technical advisory reports.
- Degree in Computer Science, Engineering, or equivalent commercial experience.
- 5+ years in cloud architecture for SaaS platforms.
- Proven experience designing and scaling secure, multi-tenant systems on AWS, Azure, or Google Cloud.
- Strong understanding of DevOps, MLOps, CI/CD pipelines, GPU orchestration, and containerisation (e.g., Kubernetes with NVIDIA support).
- Knowledge of scalable architectures for burst processing and distributed systems.
- Excellent interpersonal and communication skills.
- Experience with GPU-accelerated real-time video processing and edge computing.
- Background in commercialising SaaS products, ideally in a startup environment.
- Knowledge of MLOps tools (e.g., KServe, Triton, MLflow, Kubeflow).