• 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.