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Urgent! Sr. DevOps Engineer - AI Job Opening In ThoUSAnd Oaks California – Now Hiring Talent Space

Sr. DevOps Engineer AI



Job description


We’re looking for a skilled Cloud DevOps Engineer with a strong background in cloud infrastructure, automation, and DevOps for a contract to hire opportuntiy in Thousand Oaks, CA!



What You'll Do:





  • Design, implement, and manage scalable, reliable infrastructure in AWS to support high-availability systems.




  • Build and maintain Windows and Linux server environments, ensuring seamless integration across hybrid and cloud platforms.




  • Use Infrastructure as Code (IaC) tools like AWS CloudFormation, CDK, Terraform, and OpenTofu to automate infrastructure provisioning and configuration.




  • Implement configuration management using Chef to maintain consistency across Windows and Linux systems.




  • Design and optimize CI/CD pipelines using GitLab CI/CD, supporting automated deployment workflows for .NET applications.




  • Integrate generative AI services such as AWS Bedrock, Google Agentspace, and similar tools into the platform to support scalable and secure AI delivery.




  • Develop infrastructure to support large-scale AI/ML pipelines for model training, inference, and deployment across AWS and GCP environments.




  • Automate the full AI/ML model lifecycle—training, deployment, monitoring—ensuring reproducibility and smooth collaboration between data science and engineering teams.




  • Partner with AI engineers to deliver reusable APIs, scalable infrastructure, and tools that accelerate innovation and adoption of machine learning across the organization.




  • Implement robust observability, cost management, and security/privacy strategies tailored to AI workloads, including resource-efficient scaling and monitoring of inference services.




  • Ensure infrastructure and deployment security aligns with best practices and compliance standards.




  • Collaborate with software engineering teams to understand their needs and provide DevOps solutions that improve velocity and reliability.




  • Troubleshoot and resolve infrastructure or deployment issues across environments.




  • Deploy and manage monitoring and logging systems to ensure real-time visibility and proactive issue detection.




  • Contribute to the creation and documentation of internal DevOps best practices, standards, and tooling.




  • Stay current with evolving trends in cloud infrastructure, DevOps automation, and AI platform engineering.




  • Offer mentorship and support to junior team members, helping grow the team’s technical capabilities.



    Qualifications:

     



    Qualifications:




  • Bachelor’s degree in Computer Science, Engineering, or a related field — or equivalent practical experience.




  • 5+ years of professional experience in a DevOps or Site Reliability Engineering (SRE) role, with a strong track record of supporting production systems.




  • At least 1 year of experience working with AI services and large language models (LLMs), including integration and orchestration.




  • Extensive hands-on experience with Amazon Web Services (AWS) and cloud-native architectures.




  • Solid knowledge of both Windows and Linux server administration, including experience integrating these environments within cloud platforms.




  • Proven expertise with Infrastructure as Code (IaC) tools, particularly AWS CDK and Terraform.




  • Strong experience building and managing CI/CD pipelines, especially using GitLab CI/CD.




  • Experience deploying and maintaining .NET applications in cloud environments.




  • Deep understanding of cloud security best practices and how to implement them across infrastructure and CI/CD workflows.




  • Solid grasp of networking fundamentals, including TCP/IP, DNS, load balancing, and firewall configuration in cloud-based systems.




  • Hands-on experience with monitoring and logging tools such as New Relic, AWS CloudWatch, or similar platforms.




  • Strong scripting skills in languages such as PowerShell, Python, Ruby, or Bash.




  • Excellent problem-solving abilities and the capacity to troubleshoot complex systems efficiently.




  • Strong communication and collaboration skills, with the ability to work effectively across teams and departments.




  • Experience with containerization technologies like Docker and Kubernetes is a plus.




  • AWS and/or GCP certifications are a strong advantage.




  • Familiarity with Chef for configuration management is preferred.






Required Skill Profession

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