DevOps Architect

Join our Team

• Lead technical design discussions, architecture reviews and proof-of-concept initiatives.
• Gather and analyze metrics from operating systems and applications to support performance tuning and fault finding.
• Partner with development teams to improve services through rigorous testing and release procedures.
• Participate in system design consulting and platform management.
• Create sustainable systems and services through automation and uplifts.
• Balance feature development speed and reliability with well-defined service level objectives.
• Roll out automation in customer environments and troubleshoot during live node activities.

• Demonstrable experience in full-stack systems and software development.
• Expertise in DevOps pipeline orchestration and automation.
• Experience with public cloud platforms: Azure, AWS, GCP.
• Must have: Git, Ansible, Python, Bash scripting, JSON/YAML, Ubuntu 20.04/22.04 and RHEL 7/8.
• Also valued: Kubernetes, GitLab, Docker, Azure DevOps, GitHub, Puppet/Chef, Cloudflare Access, SonarQube (SAST), Artifactory.
• Knowledge and hands-on experience in GitOps through Flux.
• Experience with common development tools: source code management, configuration management, security and compliance, artifact repositories and monitoring tools.
• Project management skills; Scrum, Agile and DevOps ways of working (preferred).
• AI/ML architecture: Proven experience designing large-scale AI/ML solutions for production and enterprise environments.

• Programming and ML: Strong Python with hands-on PyTorch and TensorFlow experience and modern deep-learning practices.
• GenAI and LLMs: Deep understanding of LLM architectures, fine-tuning, prompt engineering, inference optimization and enterprise deployment.
• RAG and knowledge systems: Hands-on experience with RAG pipelines, embeddings, vector databases, semantic search and knowledge-grounded AI applications.
• Agentic AI: Familiarity with agentic AI frameworks, AI agents, tool calling, orchestration and integration protocols such as MCP.
• MLOps: Solid grasp of CI/CD, model lifecycle management, observability, governance, monitoring, retraining and continuous improvement.
• Enterprise architecture: Ability to translate complex business requirements into scalable, secure, resilient and cost-effective AI architectures.

• Design scalable, robust systems with development teams using cloud-native architectural principles.
• Build automation with industry-standard tools to deploy hundreds of services.
• Develop, manage and maintain automation assets of the Service Delivery Global DevOps Platform, including automation for platform infrastructure, applications and services.
• Provide primary operational support, lifecycle management and engineering for platform systems and services.

“All academic credentials must be from recognized and accredited institutions and are further subject to verification.”