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About the role
DevOps / Cloud Engineer - Python Platform & AI Services Role Summary We are looking for a DevOps / Cloud Engineer with 2 - 3 years of experience to support deployment and operations of our Python-based platform and AI services. The role involves managing Docker-based deployments, CI/CD pipelines, monitoring, cloud infrastructure, and helping the engineering team run both traditional backend services and AI workloads reliably. Key Responsibilities - Build and maintain CI/CD pipelines for Python applications. - Deploy and manage Python APIs, background services, and AI modules. - Manage Docker containers and assist with Kubernetes or container orchestration. - Configure Linux servers, Nginx, reverse proxies, and environment setup. - Monitor application performance, logs, uptime, and failures. - Support deployment of AI services, vector databases, and document-processing pipelines. - Assist with backup, security, and disaster recovery planning. - Work closely with developers to improve deployment and release processes. - Help manage environments for development, testing, staging, and production. - Ensure infrastructure follows security and data privacy standards. Mandatory Skills - Positive knowledge of Linux and server administration. - Experience with Docker and containerisation. - Experience with CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps. - Familiarity with Nginx, environment variables, and deployment troubleshooting. - Basic understanding of AWS, Azure, or Google Cloud. - Familiarity with monitoring and logging tools. - Knowledge of Git and release management. - Basic scripting skills in Python or Bash. - Basic understanding of AI workloads and requirements such as GPU usage, model hosting, or vector databases. Preferred Skills - Exposure to Kubernetes. - Experience supporting Python/FastAPI applications. - Familiarity with databases such as PostgreSQL, Redis, MongoDB, or Elasticsearch. - Exposure to AI infrastructure such as Hugging Face models, Ollama, Llama, or local model deployment. - Awareness of data privacy, secrets management, and secure handling of enterprise data. - Exposure to observability tools such as Grafana, Prometheus, ELK, or Datadog. Experience 2 - 3 years of experience in DevOps, Cloud Engineering, or Infrastructure support. Candidates with experience in Python application deployment or AI infrastructure will be preferred. DevOps / Cloud Engineer - Python Platform & AI Services Role Summary We are looking for a DevOps / Cloud Engineer with 2 - 3 years of experience to support deployment and operations of our Python-based platform and AI services. The role involves managing Docker-based deployments, CI/CD pipelines, monitoring, cloud infrastructure, and helping the engineering team run both traditional backend services and AI workloads reliably. Key Responsibilities - Build and maintain CI/CD pipelines for Python applications. - Deploy and manage Python APIs, background services, and AI modules. - Manage Docker containers and assist with Kubernetes or container orchestration. - Configure Linux servers, Nginx, reverse proxies, and environment setup. - Monitor application performance, logs, uptime, and failures. - Support deployment of AI services, vector databases, and document-processing pipelines. - Assist with backup, security, and disaster recovery planning. - Work closely with developers to improve deployment and release processes. - Help manage environments for development, testing, staging, and production. - Ensure infrastructure follows security and data privacy standards. Mandatory Skills - Positive knowledge of Linux and server administration. - Experience with Docker and containerisation. - Experience with CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps. - Familiarity with Nginx, environment variables, and deployment troubleshooting. - Basic understanding of AWS, Azure, or Google Cloud. - Familiarity with monitoring and logging tools. - Knowledge of Git and release management. - Basic scripting skills in Python or Bash. - Basic understanding of AI workloads and requirements such as GPU usage, model hosting, or vector databases. Preferred Skills - Exposure to Kubernetes. - Experience supporting Python/FastAPI applications. - Familiarity with databases such as PostgreSQL, Redis, MongoDB, or Elasticsearch. - Exposure to AI infrastructure such as Hugging Face models, Ollama, Llama, or local model deployment. - Awareness of data privacy, secrets management, and secure handling of enterprise data. - Exposure to observability tools such as Grafana, Prometheus, ELK, or Datadog. Experience 2 - 3 years of experience in DevOps, Cloud Engineering, or Infrastructure support. Candidates with experience in Python application deployment or AI infrastructure will be preferred.