Lead AI Engineer | Onsite - Delaware
Tasks
- Define LLM usage standards
- Define evaluation frameworks
- Deliver AI agent systems
- Deliver RAG systems
- Deliver multi LLM scenarios
- Design knowledgebase
- Implement AI observability
- Implement guardrails for safety compliance and PII
- Implement real time eval strategy
- Integrate AI testing into CI/CD
- Integrate tool use patterns
- Manage context windows
- Manage offshore delivery
- Own LLM API integration
- Perform code and design reviews
- Profile latency
- Report risks blockers and status
- Select vector database
- Set prompt engineering standards
- Track AI costs
- Unblock delivery issues
Perks/Benefits
Skills/Tech-stack
AI Agents | AI Observability | AWS Bedrock | Agent systems | CI/CD | Compliance | Content Safety | Context window | Context window management | Cost Management | Evaluation Frameworks | Guardrails | Knowledgebase Design | LLM | LLM API | Langchain | Latency profiling | Llamaindex | MCP | Multi-Agent | Multi-Agent Systems | PII protection | Prompt engineering | Python | RAG | Real Time | Real-time evaluation | Retrieval-Augmented Generation | SDK | Semantic Kernel | Time Evaluation | Tool use | Vector Databases | Window management
Education
N/A
Roles
AI | AI Engineer | Engineer | Lead | Lead AI | Lead AI Engineer
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