Staff Platform Engineer defining cloud and DevSecOps strategy for Robots & Pencils’ enterprise AI systems.
Leading Kubernetes, AI/ML infrastructure, migrations, reliability, security, and platform standards remotely in Canada.
Responsibilities
Define DevOps strategy and lead infrastructure architecture across multi-environment, multi-region cloud systems
Architect and own scalable Kubernetes platforms and containerized infrastructure at scale
Own infrastructure as code strategy and standards across environments
Lead DevSecOps implementation, including secrets management, compliance, auditing, IAM, and zero-trust networking
Drive platform reliability, performance SLAs, and cost optimization across production systems
Lead complex cloud migrations and platform modernization initiatives
Own observability strategy and production reliability practices
Lead AI/ML platform infrastructure design and operation, including model serving and deployment, GPU workload orchestration, LLM gateway and observability, vector store infrastructure, and CI/CD for AI/ML systems
Use modern AI assistants such as Claude and Cursor to improve delivery quality and pace
Partner with engineering, product, and leadership to align platform strategy with business and delivery goals
Communicate infrastructure decisions and tradeoffs to technical and non-technical stakeholders
Lead design reviews, architecture discussions, and release readiness assessments
Establish platform engineering standards and best practices
Mentor junior and mid-level engineers
Act as a technical escalation point for complex infrastructure and platform challenges
Evaluate emerging tools and technologies to improve platform reliability and developer experience
Requirements
7+ years of professional DevOps or platform engineering experience, including leading complex platform initiatives
Expert scripting and programming skills, such as Python, Go, Java, or Bash
Deep expertise in at least one major cloud platform
Expert Kubernetes and container orchestration skills
Expert infrastructure-as-code skills across multiple tools
Strong CI/CD architecture experience at scale
Strong DevSecOps experience, including secrets management, compliance, and auditing
Experience with networking, IAM, cloud security architecture, and zero-trust principles
Experience with service mesh, distributed systems, and microservices architecture
Strong AI/ML platform infrastructure experience, including model serving and deployment, GPU workload orchestration, LLM gateways and observability, vector store infrastructure, and CI/CD for AI/ML systems
Demonstrated leadership and technical mentoring experience
Strong stakeholder communication skills
Demonstrable day-to-day usage and expert knowledge of AI-forward tools such as Claude and Cursor
Excellent problem-solving skills and sound judgment in ambiguous technical and business challenges
Cloud certifications or FinOps experience is a plus
Helpful: HPC cluster infrastructure across AWS, CoreWeave, GCP, and OCI
Helpful: HPC job schedulers and workload managers such as Slurm or equivalent
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