AI Platform Engineer
Tasks
- Add observability for models and agents
- Build and operate LLMOps workflows
- Build and operate MLOps workflows
- Create CI CD pipelines for model training and release
- Define retrieval memory and model routing patterns
- Deploy AI services using Kubernetes
- Design deployment patterns for ML models
- Ensure reliability scalability cost optimization
- Implement agentic workflows using LangGraph
- Integrate AI services with product APIs and enterprise systems
- Manage model registry and experiment tracking
Perks/Benefits
- Accredited courses
- Disability insurance
- Donation matching
- Employee assistance program
- Employee recognition program
- Hybrid working
- Life insurance
- Medical insurance
- Online learning
- Paid time off for bereavement
- Paid time off for sick leave
- Paid time off for volunteering
- Paid time off for voting
- Retirement plan
- Unlimited vacation
Skills/Tech-stack
AI Foundry | AI Search | AKS | Agentic Workflows | Autogen | Azure AI | Azure AI Foundry | Azure AI Search | Azure Container | Azure Container Apps | Azure Functions | Azure OpenAI | CI/CD | Container Apps | CrewAI | Databricks | Docker | Drift Detection | Experiment tracking | GitHub Actions | Human-in-the-loop | Kubernetes | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model versioning | Monitoring | Observability | Python | Retrieval-Augmented Generation | Semantic Retrieval | Terraform | The Loop | Token Usage Monitoring | Token usage | Tracing | Usage monitoring | Vector Databases
Education
N/A
Roles
AI | AI Platform Engineer | Engineer | LLMOps Engineer | MLOps Engineer | Platform Engineer
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