Staff AI Engineer
Tasks
- Collaborate with cross-functional teams
- Communicate architecture decisions
- Define AI evaluation frameworks
- Define AI system architecture
- Deploy AI systems to production
- Design LLM orchestration
- Design embedding data architectures
- Ensure AI observability
- Establish MCP standards
- Evaluate emerging AI technologies
- Implement AI governance models
- Implement Human in the Loop
- Implement context management
- Implement multi-agent coordination
- Implement vector database ingestion
- Integrate LLMs with enterprise APIs
- Monitor system reliability
- Optimize latency cost accuracy
- Set up CI CD integration
- Standardize agentic AI systems
Perks/Benefits
- Child care assistance
- Education assistance
- Flexible hours
- Health and dental plan
- Health and mobility support
- Life insurance
- Meal voucher
- Optional international travel opportunities
Skills/Tech-stack
AI Services | AWS | AWS Bedrock | AWS CodeDeploy | Agent systems | Agentic AI | Arize | Azure | Azure AI | Azure AI Services | Azure Pipelines | Braintrust | CI/CD | Chunking | Context engineering | Django | Embeddings | Event Tracking | Express | Function Calling | GCP | Generative AI | GitHub Actions | Java | Jenkins | Kubernetes | LLM | Langgraph | Langsmith | MCP | Model Context Protocol | Monitoring | Multi-Agent | Multi-Agent Systems | NLP | Observability | OpenAI Eval | Prompt engineering | Python | RAG | Ragas | Spring | Tool-Calling | TypeScript | Vector Databases
Education
N/A
Roles
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