Senior AI Engineer
Tasks
- Architect LLM enabled solutions
- Build production APIs
- Conduct LLM platform evaluation
- Create reusable AI engineering frameworks
- Define governance and responsible AI controls
- Deploy generative AI solutions
- Design enterprise AI applications
- Establish CI/CD
- Implement testing and evaluation
- Integrate AI into enterprise applications
- Lead AI engineering team
- Mentor engineers
- Optimize performance and security
- Prototype and convert pilots to production
- Set up observability and monitoring
Perks/Benefits
- N/A
Skills/Tech-stack
ADLS | AI Search | AWS Bedrock | Access Control | Agentic Workflows | Anthropic Claude | Azure | Azure AI | Azure AI Search | Azure ML | Azure OpenAI | CI/CD | Cloud Architecture | Data Lineage | Data Pipelines | Data Quality | Databricks | Distributed Systems | Embeddings | FastAPI | Flask | Function Calling | Google Gemini | Human-in-the-loop | LLMOps | Langchain | Llama | Llamaindex | Logging | MLOps | Microservices | Microsoft Copilot | Mistral | Model Evaluation | Model Governance | Monitoring | Observability | OpenAI | Prompt engineering | Prompt injection | Prompt injection mitigation | Python | Responsible AI | Retrieval-Augmented Generation | Semantic Kernel | Testing | The Loop | Tool/function calling | Traceability | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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