Senior DevOps Engineer (AI Platform)

Dear Candidate,

Below is the most urgent Fulltime - Direc Hire role.

If interested in the below role then please share your updated resume with expected yearly salary and a copy of your photo ID.

Job Title: Senior DevOps Engineer (AI Platform)
Location: Fort Mill, SC (Hybrid – 3 Days Onsite)
Job Type: Full-Time (FTE)

Position Overview

We are seeking a highly skilled Senior DevOps Engineer to join our engineering team in Fort Mill, SC. This is a hands-on role requiring deep expertise in AWS, Kubernetes, Terraform, Ansible, CI/CD, Infrastructure as Code (IaC), and cloud automation.

The ideal candidate will also have exposure to AI/ML infrastructure and experience supporting Generative AI or Agentic AI applications in production.

You will work closely with Software Engineering, Platform Engineering, AI/ML teams, and Cloud Architects to build scalable, secure, and highly available cloud infrastructure while driving automation and DevOps best practices.

Key Responsibilities

Cloud Infrastructure & Automation

• Design, implement, and maintain highly available cloud infrastructure on AWS.
• Build and manage Infrastructure as Code (IaC) using Terraform.
• Automate infrastructure provisioning, configuration management, and deployments using Ansible.
• Manage cloud networking, IAM, VPCs, Load Balancers, Auto Scaling Groups, Route53, S3, EKS, EC2, RDS, Lambda, CloudWatch, and related AWS services.
• Optimize cloud environments for scalability, reliability, performance, and cost.

Kubernetes & Containerization

• Deploy and manage containerized applications using Docker and Kubernetes (EKS preferred).
• Configure Kubernetes deployments, services, ingress controllers, namespaces, ConfigMaps, Secrets, Helm Charts, and autoscaling.
• Monitor cluster health and troubleshoot production issues.
• Ensure high availability and disaster recovery strategies.

CI/CD & DevOps

• Design and maintain CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
• Automate application deployments across development, QA, staging, and production environments.
• Integrate security scanning, testing, and compliance into deployment pipelines.
• Support blue-green deployments, canary releases, and rolling deployments.

AI/ML Platform Support

• Support infrastructure for Generative AI and Agentic AI applications.
• Deploy AI workloads using Kubernetes and cloud-native services.
• Collaborate with AI/ML engineers to optimize GPU-enabled infrastructure.
• Support AI model deployment, inference services, and scalable AI platforms.
• Work with vector databases, AI APIs, or LLM-based applications (preferred).

Monitoring & Production Support

• Implement monitoring and alerting using Prometheus, Grafana, CloudWatch, Datadog, ELK, or Splunk.
• Troubleshoot production issues and perform root cause analysis.
• Ensure system uptime, reliability, and performance.
• Participate in production support and incident management.

Security & Best Practices

• Implement IAM policies and cloud security best practices.
• Ensure infrastructure complies with organizational security standards.
• Manage secrets, certificates, and secure deployment practices.
• Collaborate with Security and Infrastructure teams on governance and compliance initiatives.

Required Qualifications

• Bachelor''s degree in Computer Science, Information Technology, or related field.
• 7+ years of DevOps or Cloud Engineering experience.
• Strong hands-on experience with AWS Cloud.
• Extensive experience with Kubernetes (EKS preferred).
• Strong expertise in Terraform for Infrastructure as Code.
• Hands-on experience with Ansible for configuration management and automation.
• Strong experience with Docker and container orchestration.
• Experience building and maintaining CI/CD pipelines.
• Strong Linux administration and troubleshooting skills.
• Experience with Git, branching strategies, and version control.
• Proficiency in scripting using Python and/or Shell (Bash).
• Strong understanding of networking, DNS, SSL/TLS, IAM, security groups, and load balancing.
• Excellent troubleshooting and production support experience.

Preferred Qualifications

• Experience supporting Generative AI, LLM, or Agentic AI workloads.
• Experience deploying AI/ML models into production.
• Exposure to LangChain, OpenAI APIs, Hugging Face, Bedrock, Vertex AI, or Azure OpenAI.
• Experience with GPU-enabled Kubernetes clusters.
• Knowledge of MLOps concepts and AI infrastructure.
• Experience with GitOps tools such as ArgoCD or FluxCD.
• AWS Solutions Architect, AWS DevOps Engineer, CKA, CKAD, or Terraform certifications are a plus.