Platform Engineer – Data Science & AI Platform
London, England, United Kingdom
GBP 75K-90K (estimate) Senior-level Full Time
Tasks
- 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
Skills/Tech-stack
ACL | Access Management | AgentOps | Apache Spark | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | Azure Databricks | Azure DevOps | Azure Virtual | Azure Virtual Network | CI/CD | Data Lake Storage Gen2 | Data Lineage | Data Quality | Docker | Entra ID | Experiment tracking | GitHub Actions | Identity and Access Management | Identity and access | Infrastructure as Code | Kubernetes | LLM Gateway | Model Monitoring | Network Security | Network Security Groups | Observability | Private Endpoint | Prompt engineering | Python | RBAC | Secure Configuration | Security groups | Terraform | Unity Catalog | Virtual Network | “as-code”
Education
N/A
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