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Platform Engineer – Data Science & AI Platform

Summary

Build and maintain the AI/ML platform infrastructure, including data pipelines, observability, and governance, using Python, Spark, and IaC while collaborating with data scientists and engineers.

- Add observability for agent traces responses evaluations and monitoring - Apply security and compliance best practices with RBAC and ACLs and identity and access management - Build and evolve data and ML platform infrastructure - Collaborate with data engineers data scientists and ML engineers - Create documentation standards and best practices - Develop data processing components with Python and Spark - Enhance observability for data quality pipeline reliability and model performance - Implement data and ML governance with lineage and permissions - Implement evaluation pipelines and safety guardrails - Implement infrastructure-as-code - Improve platform reliability, performance, and security - Maintain shared datasets and platform services - Manage Dev/Test/Prod environments - Manage access control and secure configuration - Manage data and ML lifecycle with pipelines experiment tracking and versioning - Operate agentops capabilities including LLM gateway tool integration and prompt version management - Set up CI/CD pipelines Perks/Benefits: - Employee discount - Employee sample sales - Fixed annual payment - Paid annual leave - Personalised learning - Private medical care scheme

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