Applied AI Engineer (Agentic AI & ML)
Tasks
- Build CI/CD pipelines
- Build RAG pipelines
- Convert prototypes into reusable components
- Create evaluation frameworks and guardrails
- Decompose ambiguous problems
- Deploy models and applications to cloud
- Design and build agentic AI systems
- Develop backend APIs and services
- Ensure reliability performance cost and security
- Identify AI use cases and scope solutions
- Implement LLM prompt engineering
- Implement observability and monitoring
- Integrate AI into enterprise systems
- Maintain and improve ML DL models
- Operate production AI systems
- Orchestrate multi-agent workflows
- Retrain and evaluate models
- Route field learnings to platform tooling and roadmap
Perks/Benefits
- N/A
Skills/Tech-stack
.NET | AKS | API Design | Agent Orchestration | Agentic AI | App Service | Azure | Azure App | Azure App Service | Azure DevOps | Azure Functions | Azure OpenAI | C# | CI/CD | Deep learning | Docker | Forecasting | GCP | LLM | LLM orchestration | LLM orchestration frameworks | MCP | Machine Learning | Model Context Protocol | Multi-Agent | Multi-agent orchestration | NodeJs | Orchestration frameworks | Prompt engineering | Python | RAG | REST API | REST API design | REST APIs | Retrieval-Augmented Generation | Series modeling | Time Series | Time Series Modeling | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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