AI Data Engineer
Remote (United States)
R
USD 140K-207K (estimate) Senior-level Full Time
Tasks
- Build data and AI platforms as code
- Collaborate with security governance and IT operations teams
- Create CI CD pipelines and automated testing
- Curate index and refresh data sources for RAG
- Design and maintain scalable ETL and ELT pipelines
- Design build and operate data and AI platforms
- Detect data drift and distribution shifts
- Enable batch and near real time inference pipelines
- Enable observability for data and model performance
- Generate embeddings and manage embedding lifecycle
- Implement GitOps workflows and pull request change control
- Implement data quality monitoring and schema integrity checks
- Implement feature engineering and feature store workflows
- Implement model versioning and retraining and rollback strategies
- Ingest and maintain vector databases
- Integrate security privacy and compliance controls into pipelines
- Maintain auditable data lineage and documentation
- Maintain infrastructure as code for data and AI systems
- Monitor pipeline performance and failure modes
- Operate Azure based data and AI platforms
- Operationalize ML models with MLOps workflows
- Optimize platform cost efficiency performance reliability and scale
- Produce architecture diagrams runbooks and operational documentation
- Support AI ML model training and retraining
- Support hybrid and restricted enterprise environments
- Translate AI and business requirements into enterprise architectures
Perks/Benefits
- Career growth opportunities
- Continuous learning and development opportunities
- Health benefits
- Remote-first work environment
- Team collaboration culture
Skills/Tech-stack
AWS | Application Insights | Azure | Azure Container | Azure Container Registry | Azure DevOps | Azure Kubernetes | Azure Kubernetes Service | Azure ML | Azure ML Model Registry | Azure Machine Learning | Azure Monitor | Azure OpenAI | Azure Storage | Batch inference | CI/CD | Container Registry | Databricks Feature Store | ELT | ETL | Embeddings | Feature Store | GitHub | GitOps | Infrastructure as Code | JSON | Kubernetes Service | LLM Operations | Language Models | Large Language Models | MLOps | Machine Learning | Machine learning monitoring | Model Registry | Model versioning | Near Real Time Inference | Near-real-time | Python | RAG | Real-time Inference | Retrieval-Augmented Generation | SQL | Shell Scripting | Terraform | Vector Database | Vector Search | YAML | “as-code”
Education
Roles
AI | AI Data Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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