(Summary generated by AI based on the full job description)
The project focuses on implementing enterprise-scale AI solutions with emphasis on generative and agentic capabilities. The stack includes Python, Generative AI, LangChain and LangGraph, and infrastructure: Kubernetes, Docker, Kafka, Apigee, MLOps and observability tools (e.g. MLflow, Seldon, Arize) and data technologies: Spark, dbt, Delta Lake, Parquet. Responsibilities include designing and implementing production-grade GenAI and agent services, translating requirements into architecture, deployment automation and monitoring, supporting MLOps, removing technical blockers and participating in technical decisions and Agile ceremonies.




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