AI Engineer (Energy)
Aurum Q2, IN - India
R
INR 1860K-2700K (estimate) Mid-level Full Time
Tasks
- Analyze usage patterns and user feedback
- Automate infrastructure operations
- Build RAG solutions
- Build copilots and multi agent systems
- Configure monitoring, logging, and alerting
- Create technical documentation and deployment guides
- Deploy solutions on Microsoft Azure
- Design AI applications
- Design APIs and data pipelines
- Develop prompt engineering solutions
- Ensure AI policy compliance and cybersecurity
- Establish AI deployment pipelines
- Execute model testing and validation
- Implement CI/CD pipelines
- Implement agent orchestration and tool calling
- Implement model governance and version control
- Implement vector search
- Integrate AI with enterprise systems
- Manage AI lifecycle development testing validation deployment monitoring retirement
- Measure model accuracy and business performance
- Monitor token consumption and cloud costs
- Run AI evaluation frameworks
- Support pilots and production rollouts
- Support risk assessments and architecture reviews
- Troubleshoot production issues
Perks/Benefits
Skills/Tech-stack
AI Foundry | API Design | Alerting | Azure | Azure AI | Azure AI Foundry | Azure Functions | Azure OpenAI | Azure Pipelines | By Design | CI/CD | Copilot Studio | Data Pipelines | Embeddings | FinOps | GitHub | Graph API | Guardrails | Human-in-the-loop | Infrastructure as Code | JSON | Logging | Logic Apps | Microsoft 365 | Microsoft 365 Copilot | Microsoft Copilot | Microsoft Copilot Studio | Microsoft Graph | Microsoft Graph API | Model Governance | Monitoring | Observability | Orchestration | Power Platform | Python | RAG | REST APIs | Retrieval-Augmented Generation | Security by design | Semantic Search | The Loop | Tool-Calling | Vector Search | Version control | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | MLOps Engineer
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