Staff AI Engineer
Tasks
- Build LLM powered applications with APIs and data pipelines
- Build datasets and test cases for agent validation
- Contribute to AI platform architecture and engineering decisions
- Debug and improve multi step system reliability
- Define model performance metrics for real workflows
- Design agentic workflows with tool use and retrieval
- Design and build LLM harnesses for production execution
- Design pipelines combining retrieval structured data and reasoning
- Develop reusable context management and orchestration abstractions
- Implement logging tracing and monitoring for agent behavior
- Implement prompt management and context injection frameworks
- Integrate AI capabilities into production backend services
- Mentor engineers on AI engineering practices
- Optimize latency cost and scalability of AI systems
- Partner with Product Data and Science teams on AI solutions
- Use evaluation frameworks to measure correctness reliability and safety
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Agentic Workflows | Context Management | Cost Optimization | Data Pipelines | Dataset Building | Evaluation | LLM harness | Language Models | Large Language Models | Latency optimization | Logging | Model metrics | Monitoring | Orchestration | Production reliability | Prompt engineering | RAG | Retrieval-Augmented Generation | Scalability | System design | Testing | Tool use | Tracing
Education
N/A
Roles
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