AI Engineer (FTE / Hybrid)
Tasks
- Build GraphQL APIs
- Build REST APIs
- Build semantic search solutions
- Deploy AI models to production
- Design machine learning models
- Develop AI automation solutions
- Document solution architectures
- Ensure responsible AI practices
- Implement vector embeddings
- Integrate AI models with enterprise applications
- Maintain AI model performance
- Maintain change control processes
- Monitor AI solutions in production
- Perform model lifecycle monitoring
- Provide incident support for AI solutions
- Support AI governance and enablement
- Support enterprise AI strategy
- Troubleshoot AI incidents
- Use Azure AI services
- Use Copilot Studio
- Use Power Platform AI Builder
Perks/Benefits
Skills/Tech-stack
Anomaly Detection | Azure AI | Azure Machine Learning | Data Privacy | Data fairness | Dimension Table | Dimensional Modeling | Embeddings | Fact Table | Fine Tuning | GraphQL | Incident Response | Langchain | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Microsoft 365 | Microsoft Power | Microsoft Power Apps | Microsoft Power Automate | Natural Language | Natural Language Processing | Power Apps | Power Automate | Python | RAG | REST API | Responsible AI | SQL | Semantic Search | Supervised Learning | Unsupervised Learning | Vector Database
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Technology
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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