Principal AI Software Engineer
Tasks
- Build agentic AI systems
- Coordinate multi-agent systems
- Define AI platform architecture
- Define SLIs and SLOs
- Design model serving systems
- Enforce AI safety policies
- Establish AgentOps and LLMOps practices
- Implement secrets management integration
- Implement tool calling services
- Integrate enterprise APIs and identity
- Integrate vector retrieval
- Lead design and code reviews
- Manage incident analysis and follow up
- Manage state and consistency
- Mentor engineers and set engineering standards
- Optimize inference for cost and performance
- Orchestrate LLM workflows
- Perform regression testing
- Plan rollouts for AI services
- Run tracing monitoring and evals
- Set service boundaries and APIs
Perks/Benefits
- 401k match
- Commuter benefits
- Dental insurance
- Flexible spending accounts
- Life insurance
- Long-term disability
- Medical insurance
- Paid Holidays
- Paid parental leave
- Paid sick leave
- Paid time off
- Short-term disability
- Vision insurance
Skills/Tech-stack
Access Control | AgentOps | Audit Logs | Auditability | Autogen | Cloud infrastructure | Context Management | CrewAI | Docker | Embeddings | Fault Tolerance | Function Calling | GPU Inference | Human-in-the-loop | Inference Optimization | Kubernetes | LLM Evaluation | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | Model Context Protocol | Model Serving | Monitoring | Multi-tenant | Multi-tenant Security | Observability | Oracle Cloud | Oracle Cloud Infrastructure | Policy enforcement | Prompt engineering | Python | RAG | Retrieval | SLIs | SLOs | Scalability | Security Governance | Structured outputs | Tenant Security | The Loop | Tool-Calling | Tracing | Vector Databases
Education
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