LLM Application Engineer
Tasks
- Build LLM-powered applications
- Build evaluation frameworks and datasets
- Debug AI systems across model and backend stack
- Design AI agent workflows
- Develop prompting and context engineering
- Establish observability tracing and experimentation practices
- Implement tool calling workflows
- Integrate LLMs with tools and APIs
- Optimize quality latency and cost
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Agent Frameworks | Backend Services | Context engineering | Database Integration | Distributed Systems | Evaluation | Experimentation | Information Retrieval | JAX | LLM APIs | Observability | Open-weight models | OpenAI Compatible | OpenAI Compatible APIs | Orchestration | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Structured Output | Tool-Calling | Tracing | Vector Databases
Education
N/A
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