Staff Platform Engineer

Robots and Pencils•Seattle, WA

1d•Remote

About The Position

Staff Platform Engineer This role is remote based with a preference for candidates in the Seattle metro. Company Overview 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. Position Overview We’re looking for a Staff Platform Engineer to define and lead platform engineering strategy across complex, multi-environment cloud systems. This role is ideal for an experienced engineer who can own infrastructure architecture end-to-end, drive DevSecOps and compliance practices, and serve as a technical leader on the engagements they support. In this role, you will work as a key technical contributor on a cross-functional team, defining standards and owning platform reliability, performance, and security at scale. You’ll mentor engineers, partner with leadership on infrastructure direction, and lead complex migrations and modernization initiatives. Why This Role Matters 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.

Requirements

7+ years of professional DevOps or platform engineering experience, with experience leading complex platform initiatives
Expert scripting and programming skills (e.g., Python, Go, Java, Bash)
Deep cloud expertise across at least one major platform
Expert Kubernetes and container orchestration skills
Expert IaC 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
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
Demonstrated leadership and technical mentoring experience across a team or organization
Strong stakeholder communication skills, with 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
Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment

Nice To Haves

Cloud certifications (e.g., AWS DevOps Engineer Professional, CKA, Azure DevOps Engineer) or FinOps experience 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.

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
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
Partner with engineering, product, and leadership to align platform strategy with business and delivery goals
Communicate complex infrastructure decisions and tradeoffs clearly to technical and non-technical stakeholders
Lead design reviews, architecture discussions, and release readiness assessments
Establish platform engineering standards and best practices on the engagements you support
Mentor junior and mid-level engineers, helping them grow their craft, confidence, and impact
Act as a technical escalation point on complex infrastructure and platform challenges
Evaluate emerging tools and technologies, recommending patterns that improve platform reliability and developer experience