AI Engineer
Tasks
- Add human in the loop controls
- Apply security controls
- Architect LLM enabled solutions
- Build Retrieval-Augmented Generation solutions
- Build production services and APIs
- Create AI engineering frameworks and reference architectures
- Create agentic workflows
- Define adoption impact metrics
- Deploy AI applications
- Design enterprise AI applications
- Develop generative AI applications
- Develop tool function calling
- Establish CI/CD practices
- Establish governance controls
- Evaluate LLM platforms
- Implement observability
- Implement responsible AI controls
- Implement vector search
- Integrate AI into enterprise applications
- Mentor AI engineers and lead teams
- Monitor and mitigate prompt injection risks
- Optimize performance
- Orchestrate LLM models
- Partner with Risk and Compliance teams
- Perform model evaluation
- Prototype and convert pilots
- Support production incident management
Perks/Benefits
- N/A
Skills/Tech-stack
AI Search | API Design | Agentic Workflows | Azure AI | Azure AI Search | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure ML | Azure OpenAI | CI/CD | Cloud Architecture | Data Lake Storage | Data Pipelines | Data Privacy | Databricks | Distributed Systems | FastAPI | Flask | LLM orchestration | LLMOps | Langchain | Llamaindex | MLOps | Microservices | Model Evaluation | Monitoring | Observability | Prompt engineering | Prompt injection | Prompt injection mitigation | Python | Responsible AI | Retrieval-Augmented Generation | Security | Semantic Embeddings | Semantic Kernel | Testing | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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