Qualifications 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 Open Shift, 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-MGood knowledge of Logging and Monitoring tools, such as Splunk and Geneos. Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, Open Telemetry. Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.
