AI Engineer
Tasks
- Apply governance and security controls in code
- Build LLM powered features
- Build generative AI applications
- Deploy and operate AI workloads on Azure
- Design AI solutions
- Develop AI agents and multi-agent systems
- Develop APIs and microservices for AI capabilities
- Implement prompt injection defenses and content filtering
- Implement rag pipelines
- Implement responsible AI practices
- Implement scale reliability and backward compatibility
- Integrate AI with enterprise platforms
- Manage RBAC and least privilege access
- Set up audit logging and traceability
Perks/Benefits
- Employee resource groups
- Flexible leave
- Global Wellbeing Days
- Inclusive work environment
- Paid time off
- Remote work flexibility
Skills/Tech-stack
AI Agents | AI Foundry | AI Search | AI Studio | API Versioning | Agent systems | Audit Logging | Automated Evaluation | Azure AI | Azure AI Foundry | Azure AI Search | Azure AI Studio | Azure OpenAI | Azure OpenAI Service | Context Management | Copilot Studio | Data Classification | Event Driven | Event-driven architecture | Experiment tracking | GRPC | Generative AI | Injection Defense | Language Models | Large Language Models | MLOps | Microsoft 365 | Microsoft 365 Copilot | Microsoft Copilot | Microsoft Copilot Studio | Model versioning | Monitoring | Multi-Agent | Multi-Agent Systems | OpenAI Service | PII handling | Prompt engineering | Prompt injection | Prompt injection defense | Prompt versioning | Python | RAG | RBAC | REST APIs | Structured outputs | Tool use
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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