Senior DevOps Engineer (AI & Platform Operations)

DCG is a space where business needs and people's ambitions meet. They help candidates find an environment to grow and assist companies in building effective teams. They work closely with people and organizations, listening and responding to what matters to them, creating lasting and valuable relationships.

• Hands-on experience with Docker containerization and Kubernetes orchestration
• Experience working with CI/CD tools, including Jenkins and Maven
• Experience with Infrastructure as Code using Ansible
• Experience working with relational databases such as Oracle and DB2
• Basic knowledge of application technologies including Spring, Hibernate, XML, JSON, and Kafka
• Advanced troubleshooting experience using Splunk, Apica, and Sysdig
• Experience with modern observability tools, such as Prometheus, Grafana, and preferably the ELK stack
• Experience with AI/ML operations (MLOps) and AI agent deployments
• Knowledge of AI model serving platforms and ML workload containerization
• Understanding of AI agent orchestration and workflow automation
• Experience implementing innovative solutions using emerging technologies
• Ability to evaluate and integrate new DevOps tools and practices
• Very good command of English, both spoken and written

Nice to have:

• Software development knowledge in Java / J2EE
• Experience working with cloud platforms, such as AWS, Azure, or GCP
• Experience with IBM DataStage

• Lead Root Cause Analysis (RCA) processes and implement preventive measures for incident and problem management
• Monitor, analyze, and optimize service performance and stability in production support
• Build, maintain, and enhance deployment pipelines for multiple APIs (CI/CD management)
• Maintain Pre-Production and Production environments
• Collaborate closely with Platform Operations teams and delivery factory
• Build comprehensive runbooks and knowledge base for operational procedures
• Evaluate and implement new DevOps tools, practices, and AI-powered solutions
• Implement Infrastructure as Code practices
• Drive automation and self-healing infrastructure solutions
• Support AI/ML workload deployments and operations
• Lead adoption of emerging technologies and best practices