Staff Platform Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the design and execution of CI/CD pipelines from start to finish, ensuring quality and reliability in delivery workflows.

• Architect and develop cloud-native infrastructure solutions that focus on scalability, resilience, and cost-effectiveness.

• Design and oversee Kubernetes clusters and containerized workloads at scale.

• Implement and maintain infrastructure as code across various environments.

• Drive observability efforts, optimize performance, and manage alerting for production systems.

• Implement DevSecOps practices, including security scanning, secrets management, and access control measures.

• Lead incident response for production issues, conduct root cause analysis, and facilitate post-mortem reviews.

• Design and manage infrastructure for AI/ML platforms, including model serving and deployment, GPU workload orchestration, LLM gateway observability, vector store infrastructure, and CI/CD for AI/ML systems.

• Utilize tools like Claude, Cursor, and other contemporary AI assistants to enhance the quality and speed of work produced.

• Collaborate with engineering, QA, and product teams throughout the full Software Development Life Cycle (SDLC) to ensure alignment between infrastructure and delivery objectives.

• Effectively communicate technical trade-offs and infrastructure decisions across various functions.

• Participate in design reviews, sprint ceremonies, and release planning sessions.

• Lead platform initiatives from beginning to end while taking on increasing responsibility for infrastructure strategy.

• Contribute to the establishment of platform standards and best practices that enhance reliability and consistency.

• Begin mentoring junior engineers, sharing expertise, and fostering their professional development.

⛳️ Requirements

• 5–7 years of professional experience in DevOps or platform engineering with escalating responsibility for infrastructure.

• Proficient in scripting and programming languages such as Python, Go, and Bash.

• Hands-on expertise with at least one major cloud platform, demonstrating multi-service understanding.

• Strong experience with Kubernetes and container orchestration.

• Solid knowledge of infrastructure as code principles.

• Proven experience in designing and owning CI/CD pipelines.

• Familiarity with observability stacks.

• Knowledge of networking, security, and IAM within cloud environments.

• Understanding of microservices and distributed systems architecture.

• Experience with AI/ML platform infrastructure, including model serving and deployment, GPU workload orchestration, LLM gateway observability, vector store infrastructure, and CI/CD for AI/ML systems.

• Regular use of AI-forward tools such as Claude and Cursor.

• Excellent problem-solving abilities and capacity to tackle ambiguous technical challenges with sound judgment.

• Extensive hands-on experience with Amazon EKS, including the design, creation, and maintenance of reusable AWS CDK constructs.

• A background check may be required upon successful application.

• Experience with service mesh, multi-cloud or hybrid environments, or holding a cloud certification is a plus.

🏝️ Benefits

• Paid time off

• Medical insurance

• Dental insurance

• Vision insurance

• 401(k)