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Senior DevOps Engineer (AI Platform)Anveta • United States
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Senior DevOps Engineer (AI Platform)

Anveta
  • US
    United States
  • US
    United States
Apply Now

About

Job Title: Senior DevOps Engineer (AI Platform) Location:
Fort Mill, SC (Hybrid - 3 Days Onsite)
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. Required Technical Skills
AWS (EC2, EKS, S3, IAM, Lambda, CloudWatch, RDS, VPC) Kubernetes (EKS) Docker Terraform Ansible Jenkins / GitHub Actions / GitLab CI Python Bash Linux Git Helm Prometheus Grafana Datadog ELK Cloud Security Infrastructure as Code CI/CD AI Infrastructure Generative AI (Preferred) Agentic AI (Preferred) Nice to Have
Experience with
LaunchDarkly MLOps experience Vector databases (Pinecone, Weaviate, FAISS) LangChain OpenAI / Azure OpenAI Bedrock Kafka ArgoCD FinOps and cloud cost optimization
  • United States

Languages

  • English
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