Lead DevOps Engineer

Kforce has a client that is seeking a Lead DevOps Engineer in West Valley City, UT. Summary: 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
• 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

• 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
• Strong background in designing highly available, mission-critical platforms supporting enterprise-scale workloads