AI Engineer
Tasks
- Build API layers for AI
- Build LLM applications
- Build cloud native AI ML pipelines
- Collaborate with business stakeholders
- Create backend services for AI
- Deploy and monitor models
- Design AI/ML solutions
- Design agent orchestration
- Develop data integration workflows
- Develop generative AI applications
- Develop intelligent agents
- Ensure security and governance
- Evaluate AI technologies via prototypes
- Implement LLMOps practices
- Implement MLOps practices
- Implement rag pipelines
- Implement responsible AI controls
- Operationalize AI solutions
- Translate requirements into technical solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AI Safety | API Development | AWS | Agent Orchestration | Azure | Bias monitoring | CI/CD | Data Pipelines | Databricks | Explainability | Hugging Face | LLMOps | Langchain | Langgraph | MLOps | Microservices | Microsoft Fabric | Model Deployment | Model Monitoring | Model Validation | OpenAI | Prompt engineering | PyTorch | Python | RAG | SQL | Semantic Search | Spark | TensorFlow | Vector embeddings
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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