Full Stack AI Engineer
Summary
Build and deploy AI models end-to-end, from data pipelines to APIs and user dashboards, using Python, Kubernetes, and Azure.
- Design and implement end-to-end AI solutions from data ingestion and preprocessing to model deployment and monitoring
- Develop and optimize machine learning algorithms and deep learning models for various applications ensuring scalability and performance
- Build robust APIs and microservices to integrate AI models into existing software architectures and applications
- Create user-friendly interfaces and dashboards for interacting with AI systems and visualizing model outputs
- System design & architecture (microservices, agent-based systems)
- REST API & gRPC integration
- Python backend development
- Kubernetes/AKS, Helm, progressive delivery (canary/blue-green)
- Azure cloud services, APIM
- Semantic Kernel / Microsoft Agent Framework (or similar agent orchestration frameworks) good to have
- SSE streaming & async job/task management
- MongoDB / Cosmos DB
- Logging, monitoring & observability (Dynatrace, OpenTelemetry good to have)
- CI/CD pipelines
- JWT/OAuth2 authentication patterns