Senior AI Engineer / AI Architect
Tasks
- Build operate production ready AI systems batch real time APIs
- Define AI and MLOps reference architectures patterns and best practices
- Design develop train fine tune deploy machine learning models
- Design end to end AI architectures data ingestion feature engineering model training serving monitoring
- Design security governance and regulatory compliant AI architectures
- Develop multi cloud and hybrid cloud AI architecture
- Govern AI solutions on Google Cloud Platform and Microsoft Azure
- Implement MLOps pipelines with CI CD model versioning monitoring retraining
- Integrate AI solutions into enterprise applications and data platforms
- Lead technical team and contribute to pre sales delivery
- Mentor AI engineers and data scientists
- Optimize cloud cost scalability availability and security
- Optimize performance scalability reliability cost of AI workloads
- Select evaluate AI and MLOps technologies and frameworks
- Support AI platform governance and continuous improvement
Perks/Benefits
- N/A
Skills/Tech-stack
Azure Data | Azure Data Factory | Azure Kubernetes | Azure Kubernetes Service | Azure ML | Azure Synapse | BigQuery | Blob Storage | CI/CD | Cloud Storage | Cloud platform | DVC | Data ETL | Data Factory | Data Modeling | Dataflow | Deep learning | Entra ID | GKE | Generative AI | Google Cloud | Google Cloud Platform | IAM | Infrastructure as Code | Kubernetes Service | MLOps | MLflow | Machine Learning | Microsoft Azure | Python | SQL | Scala | Software Architecture | Solution architecture | Vertex AI | Weights and Biases | “as-code”
Education
Roles
AI | AI Architect | AI Engineer | Architect | Engineer | Senior AI Engineer
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