Do you love a career where you Experience  , Grow & Contribute at the same time, while earning at least 10% above the market? If so, we are excited to have bumped onto you. 
 Learn how we are redefining the   meaning of work  , and be a part of the team raved by Clients, Job-seekers and Employees. 
 If you are a   DevOps Engineer  looking for excitement, challenge and stability in your work, then you would be glad to come across this page. 
 We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long term project. Here are a few details. 
 Check if you are up for maximizing your earning/growth potential, leveraging our Disruptive Talent Solution. 
 Location:Charlotte, NC. 
 Exp: 3+ Years 
 We are seeking a highly skilled  DevOps Engineer  with a focus on supporting  AI/ML workloads in containerized environments  . The ideal candidate will have strong experience in deploying and managing  distributed data applications  , infrastructure-as-code (IaC) tools, and building reliable  CI/CD pipelines  . You will work at the intersection of  data engineering, machine learning operations (MLOps), and cloud infrastructure —enabling teams to build and scale next-generation AI solutions. 
 Design, deploy, and maintain  containerized environments  using  Docker  and  Kubernetes  for hosting AI and ML workloads. 
 Develop and manage  CI/CD pipelines  for model deployment and infrastructure provisioning using tools like  Terraform  ,  Ansible  , and  Git  . 
 Monitor and fine-tune the performance of  distributed systems  and AI frameworks such as: 
 Apache Spark 
 Apache Kafka 
 HBase 
 Cassandra 
 Work closely with data scientists, ML engineers, and platform teams to streamline deployment workflows and ensure infrastructure reliability. 
 Automate operational tasks and infrastructure management with a DevOps-first mindset. 
 Ensure system security, high availability, and fault-tolerance across environments. 
 Troubleshoot issues in real-time, performing root cause analysis and implementing fixes in production systems. 
5+ years  of experience in DevOps or Site Reliability Engineering roles. 
 Strong hands-on experience with  Docker  and  Kubernetes  in production environments. 
 Proven experience with  Infrastructure as Code (IaC) using  Terraform  and  Ansible  . 
 Proficient with  Git  and modern DevOps practices for CI/CD. 
 Experience with  big data / distributed systems  including  Spark  ,  Kafka  ,  HBase  , or  Cassandra  . 
 Strong understanding of system monitoring, performance tuning, and alerting for large-scale applications. 
 Familiarity with both  cloud-native tools  and  on-premise infrastructure  . 
 Excellent scripting and automation skills (e.g., Bash, Python, Go). 
 Experience supporting  ML model pipelines  or  MLOps frameworks  (e.g., MLflow, Kubeflow, SageMaker). 
 Exposure to  cloud platforms  like AWS, Azure, or GCP. 
 Knowledge of data versioning tools like  DVC  . 
 Certification in Kubernetes or a relevant cloud provider. 
 Strong communication and collaboration skills across cross-functional teams. 
 Analytical mindset with problem-solving aptitude in production systems. 
 Self-starter attitude with the ability to take ownership of complex problems. 
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