Job
Description
We are looking for a hands-on MLOps & CI/CD Engineer to join our fast-paced engineering team. This role is ideal for professionals passionate about deploying and maintaining AI/ML pipelines while enabling robust CI/CD practices across engineering projects. You will be responsible for managing the full lifecycle of machine learning models — from experimentation to deployment and monitoring — while also playing a critical role in designing and managing end-to-end CI/CD pipelines for all software components, ensuring high developer productivity and system reliability. Key Responsibilities MLOps Responsibilities Build and maintain scalable MLOps pipelines using tools like MLflow , Azure ML , or Kubeflow . Operationalise AI agents and LLM-based solutions into production-ready workflows. Deploy and maintain Retrieval-Augmented Generation (RAG) pipelines and manage vector databases . Implement model monitoring, drift detection, and retraining workflows. Collaborate with AI leads to integrate ML models via secure, optimised APIs. CI/CD & DevOps Responsibilities Design and implement CI/CD pipelines for web applications , APIs , agents , and bots . Automate build, test, and deployment processes using Azure DevOps or GitHub Actions . Manage infrastructure through Infrastructure as Code (IaC) using tools like Terraform , Bicep , or ARM templates . Standardise deployment practices across dev , staging , and production environments. Implement containerisation strategies using Docker and orchestrate using Kubernetes (AKS) . Ensure CI/CD processes include automated testing, version control, rollback strategies, and promotion policies. Enhance system observability with robust logging, monitoring, and alerting using Azure Monitor , Prometheus , or Grafana . Required Qualifications Minimum 3 years of experience in MLOps, DevOps, or CI/CD-focused roles. Proficiency in Python and YAML scripting for workflow automation. Strong hands-on experience with Azure Cloud (preferred) or AWS/GCP. Familiarity with ML tools such as MLflow , Azure ML , or Kubeflow . Experience in building and maintaining CI/CD pipelines using Azure DevOps or GitHub Actions . Proficient in Docker , Kubernetes (preferably AKS) , and secure container practices. Good understanding of RESTful APIs , web services, and microservices architecture. Experience with Git workflows ; GitOps is a plus. Bonus Points Experience with LangChain , LangGraph , or other agentic AI frameworks. Exposure to CI/CD for front-end frameworks like React or Next.js . Knowledge of security , compliance , and observability tools. Show more Show less
