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Robots and Pencils

Production-ready AI implementations for enterprises

Staff AI Platform Engineer

Platform EngineeringUpdated on Nov 14
Full-timeRemote in USA$126k - $174k

About the Job

Requirements

  • At least 7 years of professional DevOps or platform engineering experience, including experience leading complex platform initiatives.
  • Strong experience with AI/ML platform infrastructure, including model serving and deployment, GPU workload orchestration, LLM gateway and observability, vector store infrastructure, and CI/CD for AI/ML systems.
  • Experience designing and provisioning HPC cluster infrastructure using CI/CD pipelines across AWS, CoreWeave, GCP, and OCI.
  • Experience with HPC job schedulers and workload managers such as Slurm or equivalent for job submission and queue management.
  • Experience building or operating large-scale storage systems such as Lustre, NFS/POSIX, VAST, ZFS, or Hammerspace, ideally supporting AI or HPC clusters, including training data loading, checkpointing, and cross-region data movement.
  • Expert scripting and programming skills, such as Python, Go, Java, or Bash.
  • Deep cloud expertise across at least one major 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, security architecture, and zero-trust principles in cloud environments.
  • Experience with service mesh, distributed systems, and microservices architecture.
  • Demonstrated leadership and technical mentoring experience across a team or organization.
  • Strong stakeholder communication skills and the ability to translate technical depth across audiences.
  • Demonstrable day-to-day usage and expert knowledge of AI-forward tools such as Claude and Cursor.

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 the design and operation of AI/ML platform infrastructure, including model serving and deployment, GPU workload orchestration, LLM gateway and observability, vector store infrastructure, and CI/CD for AI/ML systems.
  • Use tools such as Claude, Cursor, and other modern AI assistants in daily work to deliver higher-quality work at pace.
  • Partner with engineering, product, and leadership to align platform strategy with business and delivery goals.
  • Communicate complex 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 on supported engagements.
  • Mentor junior and mid-level engineers to help them develop their craft, confidence, and impact.
  • Act as a technical escalation point for complex infrastructure and platform challenges.
  • Evaluate emerging tools and technologies and recommend patterns that improve platform reliability and developer experience.

Desired Qualifications

  • Cloud certifications, such as AWS DevOps Engineer Professional, CKA, or Azure DevOps Engineer, or FinOps experience.

About the Company

Robots and Pencils

Production-ready AI implementations for enterprises

Robots & Pencils provides enterprise AI engineering services. It builds production-ready AI systems that companies can deploy quickly, delivering measurable business impact in weeks rather than months. The team blends advanced engineering with human-centered design, combining “robots” (AI/engineering) with “pencils” (UX and product design) to create solutions that are both technically solid and easy to use. The company works with large enterprises across sectors including Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing, and operates with small, senior teams instead of large consulting firms. Its delivery centers span Canada, the U.S., Eastern Europe, and Latin America, making it a nimble alternative to traditional global system integrators. The goal is to help enterprises move quickly and confidently with AI initiatives, delivering solutions that are reliable, scalable, and aligned with real business needs.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Calgary, Canada
Founded
2009

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