LLM Application Engineer
Tasks
- Build LLM-powered applications
- Build reliable orchestration pipelines
- Create evaluation frameworks and datasets
- Debug AI systems across model and backend
- Design agent workflows
- Develop prompting and context engineering
- Implement observability tracing and experimentation
- Implement tool calling for multi step execution
- Integrate LLMs with tools and APIs
- Optimize for quality latency and cost
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agent Orchestration | Context engineering | Databases | Distributed Systems | Evaluation | Experimentation | JAX | LLM APIs | Observability | OpenAI | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Search | Structured Output | Tool-Calling | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Application Engineer | Engineer | LLM Application Engineer
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