Staff Platform Engineer
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Job Description
Senior Platform Engineer designing cloud infrastructure, CI/CD, and AI/ML platforms for an applied AI engineering firm. Driving DevSecOps, reliability, and platform strategy across enterprise systems.
Responsibilities:
- 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
- Use 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 across functions
- Participate 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 improve reliability and consistency
- Begin mentoring junior engineers, sharing knowledge and supporting their growth
Requirements:
- 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 infrastructure as code 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
- Deep hands-on experience with Amazon EKS and the ability to design, build, and maintain reusable AWS CDK constructs
- Successful completion of a background check may be required
- Experience with service mesh, multi-cloud or hybrid environments, or a cloud certification is a plus
Benefits:
- Paid time off
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)
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