Lead DevOps Engineer

Engineer

Lead DevOps Engineer

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  • Date posted
    August 19, 2026
  • Expiration date
    November 19, 2026
  • Application ends
    November 19, 2026

We are seeking a seasoned cloud and platform engineering leader to drive the design, implementation, and evolution of enterprise-scale cloud and AI infrastructure. This role will be responsible for establishing architectural direction, defining platform standards, and enabling scalable, secure, and efficient deployment of modern AI and cloud-native solutions across AWS and hybrid environments.

Key Responsibilities:

  • Define and communicate cloud infrastructure and AI platform strategies to technical teams, business leaders, and executive stakeholders
  • Provide technical leadership for platform engineering initiatives, guiding teams on architecture, best practices, and operational excellence
  • Partner with enterprise architecture and engineering teams to design and validate cloud-native solutions supporting both traditional and AI-driven workloads
  • Establish standards for AI platform operations, including model lifecycle management, inference performance, resiliency, governance, and cost optimization
  • Administer and optimize large-scale Kubernetes environments, including multi-cluster operations and workload orchestration
  • Develop observability frameworks that provide insights into platform health, reliability, performance, and operational efficiency
  • Drive automation initiatives that improve deployment speed, platform consistency, and infrastructure scalability
  • Promote Infrastructure as Code and GitOps methodologies across engineering teams
Requirements
  • 8+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or Cloud Infrastructure roles
  • Extensive hands-on experience managing Kubernetes environments at enterprise scale
  • Proven experience designing and maintaining CI/CD pipelines and GitOps-based deployment models
  • Advanced experience implementing Infrastructure as Code using tools such as Terraform, AWS CDK, or equivalent frameworks
  • Experience implementing and managing observability, monitoring, and logging solutions in large enterprise environments
  • Experience building secure and reliable AI infrastructure and supporting production AI workloads
  • Strong scripting and automation expertise using Python, Bash, or similar languages
  • Demonstrated expertise in cloud-native architecture, scalability, resiliency, and operational best practices
  • Expertise in AWS networking, including VPC design, routing, load balancing, security controls, and connectivity services
  • Deep knowledge of AWS services including compute, networking, storage, identity management, databases, and container platforms
  • Strong understanding of enterprise security principles, compliance frameworks, and audit requirements
  • Strong Linux administration and troubleshooting skills
  • Ability to mentor engineers, influence technical direction, and foster engineering excellence across teams

Preferred Qualifications:

  • Experience deploying and supporting generative AI platforms, large language models, and AI-powered applications in production environments
  • Experience with service discovery, platform networking, and distributed systems architecture
  • Prior experience leading cloud, platform, DevOps, or AI infrastructure teams
  • Familiarity with AWS AI services, including Bedrock and related AI orchestration technologies
  • Are you interested in this position?

     

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