MLOPS Engineer

. Bachelor's degree in Computer Science, Engineering, or a related field. . 4+ years of experience in Machine Learning engineering or AI system integration. . Bash and Unix/Linux command-line toolkit is a must-have. . Hands-on experience with OpenShift, Docker, Kubernetes. . Knowledge of cloud platforms (e.g. AWS) is a must-have. . Exposure to data and network security and compliance in AI systems. . Knowledge of API integration and microservices architecture. . Proficiency in Python used both for automation and ML-related tasks . Knowledge of Workflow Orchestrator, such as Ctrl-M . Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos. . Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry. . Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.