LLM Application Engineer
Tasks
- Add observability tracing experimentation and evaluation in production
- Build LLM-powered applications
- Build evaluation frameworks and datasets
- Debug AI systems across the stack
- Design AI agent workflows
- Develop prompting and context engineering
- Implement orchestration pipelines
- Implement tool calling workflows
- Integrate LLMs with APIs and tools
- Optimize models for quality latency and cost
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agentic Workflows | Backend Development | Context engineering | Databases | Distributed Systems | JAX | LLM APIs | Language Models | Large Language Models | OpenAI Compatible | OpenAI Compatible APIs | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Search APIs | Structured outputs | Tool-Calling | Vector Databases
Education
N/A
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