Principal AI Engineer, Distributed Systems & Intelligent Platforms
Tasks
- Apply engineering best practices
- Build RAG pipelines
- Build asynchronous processing pipelines
- Build backend services
- Build llm workflows
- Debug production issues
- Design distributed AI driven systems
- Develop RESTful APIs
- Generate embeddings
- Implement event-driven workflows
- Implement state machines
- Improve observability
- Lead code reviews
- Maintain cloud-native architectures
- Model NoSQL data for performance
- Monitor systems reliability
- Orchestrate multi-agent systems
- Own production systems
- Participate in technical design discussions
Perks/Benefits
- Architectural influence
- Engineering Led Collaboration
- High technical ownership
- Learning opportunities
- Remote-first work model
Skills/Tech-stack
AI Workflow Orchestration | AI workflow | AWS DynamoDB | AWS Lambda | AWS Step Functions | Agent Orchestration | Amazon EventBridge | Amazon S3 | Amazon SQS | Asynchronous processing | Composite keys | Containerization | Distributed Systems | Distributed Systems Design | Docker | Embeddings | Event Driven | Event-driven architecture | Function Calling | LLM | Multi-Agent | Multi-agent orchestration | NoSQL | Node.js | Prompt engineering | Python | RESTful APIs | Retrieval-Augmented Generation | Single Table Design | Step Functions | Systems Design | Table design | Tool-Calling | Unit Testing | Workflow Orchestration
Education
N/A
Roles
AI | AI Engineer | Backend | Backend Engineer | Distributed Systems Engineer | Engineer | Principal | Principal AI Engineer | Systems Engineer
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