Talent Space, Inc. is seeking a Senior Cloud Engineer for a contract to hire opportunity in Irvine!
Must be US Citizen or have a Green Card
You'll play a pivotal role in designing and implementing cloud solutions within a large enterprise. As part of agile team, you'll have the opportunity to work on AI and web-based products delivered in the cloud. Expertise in Kubernetes and the cloud-native ecosystem is critical to build scalable, distributed workloads.
Key Responsibilities :
Ensure all cloud infrastructure complies with industry standards and regulations (e.g., SOC 2, HIPAA, ISO 27001).
Implement best practices in cloud security, identity management, and data protection.Cost Optimization :Optimize cloud resources and services to meet budgetary goals while maintaining high-performance standards.
Design & Implementation :Utilize modern AI, tools, and approaches to designing, deploying, and managing sophisticated infrastructures.
Architect, implement, and maintain cloud-native deployment solutions for innovative applications, databases, and data orchestration pipelines.Plan, deploy, and manage Kubernetes clusters and workloads, ensuring scalability, reliability, and security.Security & Compliance :Ensure all cloud infrastructure complies with industry standards and regulations (e.g., SOC 2, HIPAA, ISO 27001).
Implement best practices in cloud security, identity management, and data protection.Innovation & Development :Develop and manage platforms for event-driven architectures (EDA), including streaming data, real-time analytics, and event processing.
Enable automated deployments of ETL pipelines, data orchestration, and AI / ML workloads optimized for cloud environments.Utilize modern design patterns to create elegant solutions for complex workloads.Infrastructure & Automation :Implement infrastructure as code (IaC) using tools like Terraform, Pulumi, Crossplane, or CloudFormation to automate infrastructure provisioning.
Collaborate with Development and DevOps teams to create and optimize CI / CD pipelines, develop containerized microservices, and ensure robust monitoring and observability.Troubleshoot, optimize, and automate cloud infrastructure to enhance system performance and reliability.Collaboration & Leadership :Work closely with cross-functional teams, including platform engineering and DevOps, to ensure design standards are met and to ensure smooth deployment and runtime support.
Mentor and develop skills across developers and engineers, fostering a culture of continuous learning and improvement.Drive continuous standards and process improvements within the team and across the organization.Minimum Qualifications :
Bachelor's degree in Computer Science, Engineering, or a related field.5 years of experience in cloud-native architecture and design within cloud environments such as AWS, Google Cloud, or Azure.Extensive experience with Kubernetes and familiarity with the CNCF ecosystem (e.g., Helm, Istio, ArgoCD, Prometheus).Hands-on experience with event-driven architectures (EDA) and event streaming platforms (e.g., Kafka, Flink).Proven experience in designing, deploying, and managing ETL pipelines and data orchestration tools (e.g., Apache Airflow, Dagster, or Prefect).Strong skills in infrastructure as code (IaC) using tools like Terraform, Pulumi, or CloudFormation.Proficiency in automation and scripting languages such as Bash, Python, or Go.Solid understanding of cloud security best practices, including network security, encryption, secrets management, and identity & access management.Experience with CI / CD pipelines, containerization (e.g., Docker), and microservices architecture.Excellent problem-solving skills with the ability to devise efficient, cost-effective, and scalable cloud-native solutions.Strong communication skills, capable of conveying complex technical concepts to both technical and non-technical stakeholders.Preferred Qualifications :
Master's degree in Computer Science, Engineering, or a related field.Certifications in AWS, GCP, or Azure cloud environments.Familiarity with AI / ML and MLOps frameworks (i.e., Jupyterlab, TensorFlow, PyTorch, Kubeflow) and integrating them into production workloads.Experience with classic and generative AI development lifecycles and self-hosting open source LLM models.Experience with monitoring and observability tools like Grafana, Prometheus, or OpenTelemetry.Demonstrated leadership experience, including mentoring team members, and driving technical initiatives.
