Senior Applied AI Engineer
Tasks
- Apply MLOps model governance and responsible AI
- Architect and build GenAI applications
- Contribute to wealth management AI strategy
- Document designs create demos support enablement and adoption
- Ensure AI performance security and regulatory compliance
- Integrate AI solutions with CRM and portfolio platforms
- Lead solution development and prototyping
- Liaise with technology teams to deploy GenAI solutions
- Monitor and improve deployed AI products
- Translate requirements into technical solutions
Perks/Benefits
Skills/Tech-stack
API Integration | AWS | AWS Lambda | Agile | Airflow | Amazon S3 | Anthropic | Autogen | Azure | Azure Blob | Azure Blob Storage | Azure Functions | Azure Machine Learning | Blob Storage | CI/CD | Copilot Studio | Copilot Studio Agents | Docker | GCP | GenAI | Google Gemini | Kubeflow | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Microservices | Model Governance | OpenAI | PyTorch | Python | Responsible AI | SageMaker | Scikit-learn | TensorFlow
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