Observability basics correlation IDs error analysis latency instrumentation, Python engineering with production hygiene testing packaging structured logging, Cloud familiarity enough to deploy and validate agents via platform pipelines not owning infra, Agentic AI frameworks patterns LangGraph LangChain CrewAI-style orchestration patterns tool function calling prompt versioning, Evaluation discipline test sets regression testing offline eval metrics A B comparisons failure taxonomy, Integration engineering APIs auth concepts schema-based tool integration MCP-style interface implementation preferred

data engineering , Docker, Kubernetes, Python, AWS, AI Engineering

C, Python, Deep Learning, Transformers

.NET, Monitoring Tools, Kafka, Grafana, JIRA, Microservices, Appdynamics, Distributed Systems, Ansible, Openshift, Splunk, Kubernetes, Python, cloud-native applications, NoSQL databases