Principal AI Engineer
Tasks
- Architect and build LLM-powered systems
- Build scalable ML platforms and pipelines
- Co define AI roadmap with leadership
- Communicate technical concepts to stakeholders
- Create AI integrated APIs and backend services
- Define AI architecture and technical strategy
- Design multi-agent orchestration
- Develop RAG solutions with vector search
- Ensure AI reliability security and scalability
- Implement logging monitoring and debugging
- Implement prompt engineering and tool calling
- Lead AI implementation lifecycle
- Lead model development and optimization to production
- Mentor engineering teams
- Orchestrate event driven asynchronous workflows
- Own high stakes architectural decisions
- Set AI engineering standards
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | API Design | AWS | AWS Bedrock | Agent Orchestration | Amazon EventBridge | Amazon SQS | Claude | Compliance | Containerization | Cursor | Debugging | Deployment Automation | Distributed Systems | Docker | Embeddings | Event Driven | Event-driven architecture | Function Calling | Language Models | Large Language Models | Logging | MLOps | Machine Learning | Model versioning | Monitoring | Multi-Agent | Multi-agent orchestration | NoSQL | Prompt engineering | Python | Reproducibility | Retrieval-Augmented Generation | SQL | Security | Streaming | System design | Tool-Calling | Unit Testing | Vector Databases | Workflow Orchestration
Education
N/A
Roles
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