Applied AI Engineer (Agentic AI & ML)
A SGD 74K-130K (estimate) Senior-level Full Time
Tasks
- Build evaluation frameworks and guardrails
- Build production grade LLM workflows
- Build secure scalable backend APIs
- Create reusable internal components and patterns
- Decompose ambiguous problems into deliverable solutions
- Deploy applications and models to cloud
- Deploy behind production authentication
- Design Agentic AI systems
- Discover AI use cases with stakeholders
- Feed learnings back to platform tooling and roadmap
- Implement CI/CD pipelines
- Implement observability and reliability monitoring
- Implement prompt engineering
- Implement rag pipelines
- Integrate agent tools and functions
- Maintain and improve production ML DL models
- Operate systems with logging and monitoring
- Orchestrate multi-agent workflows
- Retrain evaluate and tune models
Perks/Benefits
- N/A
Skills/Tech-stack
.NET | AKS | Agent Orchestration | Agent systems | App Service | Authentication | Azure | Azure App | Azure App Service | Azure DevOps | Azure Functions | Azure OpenAI | Azure Storage | C# | CI/CD | Deep learning | Docker | Function Calling | Kubernetes | Language Models | Large Language Models | Logging | MCP | Machine Learning | Model Context Protocol | Model Drift | Model Evaluation | Monitoring | Multi-Agent | Multi-Agent Systems | Node.js | Observability | Predictive Maintenance | Prompt engineering | Python | RAG | REST API | Retrieval-Augmented Generation | Security | Series forecasting | Time Series | Time Series Forecasting | Tool use | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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