Senior DevOps Engineer (вакансія неактивна)

About the Client

Our client is an AI-focused technology company that helps enterprises design, deploy, and scale reliable AI solutions. Its areas of expertise include AI consulting, MLOps, secure and on-premise LLM deployment, AI governance and guardrails, and AI-assisted modernisation of legacy software.
The company works on technically complex, business-critical solutions that require secure infrastructure, reliable deployment processes, scalable cloud environments, and strong integration between DevOps, backend engineering, and AI systems.

About the Role

We are looking for an experienced DevOps Engineer. This role is ideal for a technically strong professional who is comfortable working independently, taking full ownership of infrastructure and deployment processes, and stepping into a leadership role when required.
The successful candidate will design, maintain, and improve the technical foundation of AI-enabled products, including cloud infrastructure, CI/CD pipelines, containerised environments, GPU-based workloads, backend services, and LLM integrations.

Key Responsibilities

• Design, implement, and maintain secure, reliable, and scalable cloud infrastructure.
• Manage environments across AWS (it would be a plus to have knowledge and experience in Microsoft Azure and Google Cloud Platform).
• Build and improve CI/CD pipelines to support efficient and reliable software delivery.
• Deploy, manage, and monitor containerised applications using Docker and Kubernetes.
• Contribute to backend development, including APIs, integrations, services, and internal platforms.
• Maintain production environments and ensure system stability, performance, security, and availability.
• Implement monitoring, logging, alerting, backup, and disaster recovery processes.
• Optimize cloud infrastructure performance and cost efficiency.
• Build and maintain GPU-based environments for AI and machine learning workloads.
• Integrate and support LLM APIs and other AI services.
• Document infrastructure, deployment procedures, and operational standards.
• Collaborate with software engineers, AI specialists, product teams, and business stakeholders.

Required Skills

• Strong practical experience with AWS (it would be a plus to have knowledge and experience in Microsoft Azure and Google Cloud Platform).
• Solid experience designing and maintaining CI/CD pipelines.
• Hands-on experience with Docker and Kubernetes.
• Strong knowledge of Linux administration, cloud networking, IAM, security, and infrastructure management.
• Experience with Infrastructure as Code tools such as Terraform, Pulumi, or CloudFormation.
• Backend development experience, preferably with Python, Node.js, Go, or a comparable technology.
• Experience developing and maintaining REST APIs, backend services, and third-party integrations.
• Familiarity with monitoring and observability platforms.
• Experience managing GPU infrastructure and AI or machine learning workloads.
• Practical experience integrating LLM APIs, such as OpenAI, Azure OpenAI, Anthropic, or similar services.
• Experience with on-premise or hybrid-cloud LLM deployments.
• Upper Intermediate level of English.

We need a professional who can take ownership of the infrastructure landscape, contribute to backend engineering, support production AI systems, and help the team make reliable technical decisions.

The ideal candidate combines strong cloud and DevOps expertise with a practical development mindset, an understanding of AI infrastructure, and the maturity to take the lead when the situation requires it.