Senior Platform Engineer

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients. We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there.
We’ve earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience. We move fast, sweat the details, and build things that actually ship.

We’re looking for a Senior Platform Engineer to lead the design and delivery of cloud infrastructure, CI/CD systems, and platform tooling across complex engineering environments. This role is ideal for an experienced engineer who can architect cloud-native solutions end-to-end, enjoys hands-on development, and is growing into owning platform strategy and DevSecOps practices.

In this role, you will work as part of a cross-functional team, designing and operating scalable infrastructure, driving observability and cost management, and embedding security and compliance throughout the delivery process. You’ll collaborate closely with engineering, QA, and product teams to deliver reliable systems and develop the technical instincts that come from shipping things that matter.

At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate.
Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.

• Lead design and implementation of CI/CD pipelines end-to-end, driving quality and reliability across delivery workflows
• Architect and implement cloud-native infrastructure solutions for scalability, resilience, and cost efficiency
• Design and manage Kubernetes clusters and containerized workloads at scale
• Implement and own infrastructure as code across environments
• Drive observability, performance optimization, and alerting across production systems
• Implement DevSecOps practices including security scanning, secrets management, and access control
• Lead production incident response, root cause analysis, and post-mortems
• Design and operate 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
• Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace

• Collaborate with engineering, QA, and product teams across the full SDLC to align infrastructure with delivery goals
• Communicate technical tradeoffs and infrastructure decisions clearly across functions
• Participate actively in design reviews, sprint ceremonies, and release planning

• Lead platform work end-to-end with growing ownership of infrastructure strategy
• Contribute to platform standards and best practices that lift reliability and consistency across the team
• Begin mentoring junior engineers, sharing knowledge and supporting their growth

• 5–7 years of professional DevOps or platform engineering experience with growing ownership of infrastructure
• Strong scripting and programming skills (e.g., Python, Go, Bash)
• Hands-on cloud expertise across at least one major platform with multi-service understanding
• Strong Kubernetes and container orchestration experience
• Strong IaC expertise
• Strong CI/CD pipeline design and ownership experience
• Experience with observability stacks
• Experience with networking, security, and IAM in cloud environments
• Familiarity with microservices and distributed systems architecture
• 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
• Demonstrable, day-to-day usage of AI-forward tools such as Claude and Cursor
• Strong problem-solving skills and the ability to navigate ambiguous technical challenges with sound judgment
• Experience with service mesh, multi-cloud or hybrid environments, or a cloud certification is a plus

• A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
• A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
• Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
• Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
• Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.
• All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.
• Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you.
• Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.