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.
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