Applied AI Engineer (Agentic AI & ML)
Tasks
- Architect multi agent workflows and orchestration
- Build backend APIs and services for AI workloads
- Convert bespoke builds into reusable components and patterns
- Create evaluation frameworks and guardrails
- Decompose ambiguous problems into deliverable plans
- Deploy applications and models to Azure and GCP
- Design and build agentic AI systems with LLMs
- Ensure reliability performance cost and security
- Feed field learnings into platform tooling and roadmap
- Identify AI use cases and scope solutions
- Implement monitoring logging and observability
- Implement prompt engineering and tool calling
- Set up CI/CD pipelines
- Train evaluate tune and retrain ML DL models
Perks/Benefits
- N/A
Skills/Tech-stack
.NET | AKS | Agent Orchestration | Agent systems | App Service | Azure App | Azure App Service | Azure DevOps | Azure Functions | Azure OpenAI | Azure Storage | CI/CD | Csharp | Deep learning | Docker | Function Calling | Language Models | Large Language Models | Logging | Machine Learning | Microsoft Azure | Model Context Protocol | Monitoring | Multi-Agent | Multi-Agent Systems | NodeJs | Observability | Prompt engineering | Python | REST API | Retrieval-Augmented Generation | Tool/function calling | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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