Principal AI Engineer
Tasks
- Architect and implement agentic AI systems and multi agent orchestration
- Define success metrics and continuously optimize AI solution performance
- Design develop deploy and operate production AI applications
- Develop engineering agents to automate testing and deployment workflows
- Establish AI development best practices and evaluation frameworks
- Evaluate select and integrate AI technologies
- Implement retrieval augmented generation and retrieval strategies
- Lead end to end delivery of AI and generative AI solutions
- Monitor and improve AI models in production
- Prototype AI enabled applications and user experiences
- Provide technical leadership mentorship and architectural guidance
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | AWS SageMaker | Agent systems | Agentic AI | Automated testing | CI/CD | Code Governance | Code review | CrewAI | Databricks | Docker | Generative AI | Google ADK | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Hallucination detection | Hybrid retrieval | JavaScript | Knowledge graphs | Kubernetes | Langgraph | Language Models | Large Language Models | MCP | Machine Learning | Model Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Orchestration frameworks | Prompt engineering | Python | RAG | Red Teaming | Responsible AI | Retrieval-Augmented Generation | SQL | Safety testing | TypeScript | Vertex AI
Education
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
Regions
Countries
States
Cities
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