LLM Application Engineer
Tasks
- Build LLM-powered applications
- Build retrieval using vector databases
- Create Orchestration Pipelines
- Debug AI systems end to end
- Design agent workflows
- Develop prompting and context engineering
- Enable structured outputs and tool calling
- Implement evaluation frameworks
- Implement observability tracing experimentation
- Integrate LLMs with tools and APIs
- Optimize model quality latency and cost
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Agentic Workflows | Context engineering | Distributed Systems | Evaluation | Experimentation | Generative AI | Information Retrieval | JAX | Language Models | Large Language Models | Observability | 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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