AI Engineer
Tasks
- Build CI CD automated testing pipelines
- Create infrastructure as code
- Deliver AI and data solutions
- Deploy and manage AI systems
- Design Agentic AI systems
- Develop AI applications end to end
- Implement retrieval-augmented generation pipelines
- Maintain client stakeholder relationships
- Perform AI engineering delivery and governance
- Solve complex AI problems
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | AWS SageMaker | AWS SageMaker Pipelines | Agent systems | Agentic AI | Ansible | Anthropic API | Automated testing | Azure Machine Learning | CI/CD | Containerization | Data Versioning | Datadog | Dataiku | Docker | Fine Tuning | Google Vertex | Google Vertex AI | Hugging Face | Hugging Face Transformers | Hyperparameter Tuning | Infrastructure as Code | Jupyter | Kubeflow | Kubernetes | Langchain | Langgraph | MLflow | Machine Learning | Model Monitoring | Model Registry | Model retraining | Multi-Agent | Multi-Agent Systems | OpenAI API | Prompt engineering | PyTorch | RAG | Responsible AI | Sagemaker Pipelines | Scikit-learn | Serverless | TensorFlow | Terraform | Version control | Vertex AI | Weights and Biases | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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