AI Data / Platform Engineer
Tasks
- Apply data privacy masking and classification
- Apply hybrid retrieval with structured and unstructured data
- Build and operate data access layers and APIs
- Build retrieval systems for AI agents
- Collaborate with AI architects and engineers on agentic architectures
- Contribute reusable data patterns and reference architectures
- Define data contracts and quality expectations
- Design and implement AI data pipelines
- Enable CI CD and environment promotion for AI workloads
- Enforce access controls and identity integration
- Identify and remediate performance bottlenecks
- Implement audit logging and traceability
- Implement secure storage for prompts embeddings and artifacts
- Implement vector databases and embedding pipelines
- Ingest structured and unstructured data
- Instrument data freshness and quality monitoring
- Monitor retrieval performance and relevance
- Optimize context delivery for accuracy latency and cost
- Support model and prompt lifecycle versioning rollback and traceability
- Track usage and cost to serve
- Transform and normalize data
Perks/Benefits
- N/A
Skills/Tech-stack
API | Access Management | Audit Logging | Azure | Batch Processing | CI/CD | Cloud Architecture | Data Catalog | Data Governance | Data Pipelines | Data Privacy | Data masking | Embeddings | Identity and Access Management | Identity and access | Indexing | Observability | Python | Retrieval systems | SQL | Search | Stream processing | Vector Databases
Education
N/A
Roles
AI | AI Data Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Platform | Platform Engineer
Regions
Countries
States
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