Senior Cloud Architect designing cloud-native, data, and AI/ML systems for Robots & Pencils, an applied AI engineering firm. Building production-ready enterprise solutions across US and Canada.
Responsibilities
Contribute to architectural design across cloud, data, and AI/ML systems, taking ownership of meaningful components
Build and integrate cloud-native solutions including microservices, serverless, and containerized workloads
Implement infrastructure as code and CI/CD pipelines
Design and contribute to data architectures including pipelines, warehouses, and modeling
Support AI/ML system design, including model serving, MLOps pipelines, and integration of LLM-based capabilities
Implement monitoring, logging, and observability across deployed systems
Collaborate with engineering, data, AI, and product teams to translate requirements into technical solutions
Communicate technical tradeoffs and design decisions across functions
Maintain architecture documentation
Participate in design reviews
Take ownership of system components with growing architectural responsibility
Contribute to architectural standards and best practices
Mentor junior engineers and support their growth
Requirements
Applications from outside Canada and the US will not be considered
5+ years of professional software engineering experience, with exposure to architectural decision-making
Working knowledge of cloud platforms and cloud-native architectures, including AWS, Azure, or GCP
Proficiency in Python and at least one other language commonly used in modern stacks, such as Java, Scala, or TypeScript
Hands-on experience with containerization and orchestration, such as Docker and Kubernetes
Experience with infrastructure as code and CI/CD pipelines, such as Terraform, CloudFormation, and GitHub Actions
Working knowledge of relational and NoSQL databases, plus data pipelines and ETL/ELT concepts, such as PostgreSQL, MongoDB, Airflow, and dbt
Familiarity with AI/ML system design, including model deployment, MLOps, and LLM integration, such as SageMaker, Vertex AI, MLflow, and Hugging Face
Understanding of microservices, serverless, and event-driven architectures
Awareness of security, compliance, and observability fundamentals, such as GDPR, HIPAA, and SOC2
Demonstrable usage of AI-forward tools such as Claude and Cursor
Strong problem-solving skills and ability to navigate ambiguous technical challenges
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