LLM Application Engineer
Tasks
- Build LLM-powered applications
- Create evaluation frameworks and datasets
- Debug AI systems across model and backend
- Deliver production ready AI features
- Design agent workflows
- Implement observability tracing and experimentation
- Improve prompting and context engineering
- Integrate LLMs with APIs and tools
- Optimize AI quality latency and cost
- Orchestrate reliable tool calling and actions
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Agentic Workflows | Backend Development | Distributed Systems | Evaluation Frameworks | Experimentation | Information Retrieval | JAX | Language Models | Large Language Models | Observability | Orchestration | Prompt engineering | PyTorch | Python | Structured outputs | Tool-Calling | Tracing | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Application Engineer | Engineer | LLM Application Engineer
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