Cloud/GenAI Engineer

What is The Role

We are looking for an experienced and ambitious builder to join our Elastic IT team in the role of Cloud Engineer. In this role, you will be a primary contributor to the IT - GenAI roadmap. You will partner across IT to identify, implement and manage a portfolio of GenAI solutions that will be leveraged across our organization. This is an exciting opportunity to be a primary contributor to our AI strategy, helping design and implement AI infrastructure, custom solutions and third party SaaS offerings.

The IT Team at Elastic is seeking a talented Cloud/GenAI Engineer to strengthen our internal infrastructure and accelerate our AI initiatives. As a key member of our IT organization, you'll be responsible for architecting, implementing, and scaling cloud-native infrastructure while driving our generative AI capabilities. This role combines advanced DevOps engineering with cutting-edge AI infrastructure management.

The ideal candidate brings deep technical expertise in distributed systems, container orchestration, and infrastructure automation, with a proven track record in building resilient, scalable cloud platforms. You'll be working in a highly-distributed team environment, collaborating with global IT professionals to drive innovation and operational excellence.

What You Will Be Doing

• Develop comprehensive infrastructure as code using Terraform, including custom providers and modules
• Implement configuration management using Ansible, including custom roles and playbooks
• Create automated deployment pipelines with advanced CI/CD practices (GitOps, trunk-based development)
• Design and implement infrastructure testing frameworks and validation procedures
• Implement comprehensive observability solutions using the Elastic Stack
• Design and maintain logging architectures with log aggregation and analysis
• Implement security controls and compliance measures across the infrastructure
• Manage secrets and certificates using HashiCorp Vault and cert-manager
• Manage and optimize containerized environments using Kubernetes, including custom resource definitions (CRDs) and operators
• Implement advanced Kubernetes features like HPA/VPA, network policies, and pod security policies
• Design and maintain container image build pipelines with security scanning and optimization
• Design and implement highly available, fault-tolerant cloud infrastructure supporting internal systems and GenAI applications
• Architect multi-region Kubernetes clusters with advanced networking and security configurations
• Implement service mesh architectures for microservices communication and traffic management
• Design and maintain GitOps workflows for infrastructure and application deployment

What You Bring

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in developing generative AI models, including Natural Language Processing (NLP) or computer vision models.
• Proficiency in deep learning frameworks such as Microsoft Cognitive Services, TensorFlow, PyTorch, or Hugging Face Transformers.
• Strong knowledge of cloud platforms and services (e.g., AWS, Azure, GCP).
• Experience with containerization and orchestration (e.g., Docker, Kubernetes).
• Infrastructure as Code (Terraform, CloudFormation, ARM templates)
• Configuration management (Ansible, Salt)
• Advanced networking expertise, including overlay networks (especially VPNs), VPC configuration and management, and load balancing for performance and reliability.
• GitOps workflows (ArgoCD, Flux)
• CI/CD platforms (Jenkins, GitLab CI, GitHub Actions)
• Advanced Git workflows and branching strategies
• Experience implementing configuration as code practices beyond infrastructure provisioning, such as managing application and service configurations using tools like Ansible, Salt, or similar. Ability to design reusable, modular configuration templates that support rapid deployment and consistent environments.
• Hands-on experience with Elasticsearch, including cluster management, index lifecycle policies, and query optimization. Ability to design and maintain scalable search and analytics solutions using the Elastic Stack. Familiarity with integrating Elasticsearch into observability, logging, and monitoring workflows is highly valued.
• Proficiency in building and customizing dashboards using Kibana or other visualization tools. Ability to translate complex data into actionable insights for technical and non-technical stakeholders. Experience with dashboard automation and templating is a plus.
• Knowledge of DevOps practices for model deployment and automation.
• Strong problem-solving skills and the ability to work in a dynamic and fast-paced environment.
• Excellent communication and collaboration skills.
• Familiarity with ethical AI practices and responsible AI development.
• Strong experience with major cloud platforms (AWS, GCP, or Azure)