Senior AI Engineer
Tasks
- Build AI application layer prompt orchestration tool calling retrieval RAG embeddings agent workflows structured outputs
- Build safety and reliability guardrails ensure quality compliance operational requirements
- Design build and ship production LLM powered features end to end
- Design observability systems accuracy latency cost hallucination rates model behavior
- Develop evaluation infrastructure regression suites LLM as a judge synthetic datasets human review workflows quality metrics
- Evaluate and integrate third party orchestration frameworks evaluation platforms vector databases model providers
- Prototype quickly ship early measure outcomes iterate based on real world usage
- Provide technical leadership code reviews mentorship system design
Perks/Benefits
- N/A
Skills/Tech-stack
Agent workflows | Arize Phoenix | Compliance | Cost Optimization | Embeddings | Evaluation | Hallucination detection | Human-in-the-loop | LLM-as-a-Judge | Langchain | Langgraph | Langsmith | Language Models | Large Language Models | Latency optimization | Observability | Prompt engineering | Prompt orchestration) | Python | RAG | Regression testing | Retrieval-Augmented Generation | Safety Guardrails | Structured Output | Synthetic data | The Loop | Tool-Calling | Vector Databases
Education
N/A
Roles
Regions
Countries
States
Cities
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