Related skills
python rag hugging face orchestration embeddings📋 Description
- Collaborate with domain experts to translate needs into clear LLM prompts.
- Develop, test, and refine prompts for various use cases, ensuring accuracy.
- Troubleshoot and resolve prompt-related issues quickly.
- Design multi-step prompt workflows including agentic patterns, tool calling, and RAG.
- Work with software developers to integrate LLM solutions into Product.
- Define and maintain metrics for LLM outputs (accuracy, relevance, safety, latency, cost).
- Contribute to a scalable framework for prompt engineering across business units.
- Assist in gathering and analyzing user feedback to improve prompts.
- Stay up-to-date with LLM advancements and help select tools/platforms.
- Document prompt engineering processes and outcomes to build a knowledge base.
🎯 Requirements
- Bachelor's in CS/Engineering/Math with 4+ years in AI/ML.
- Hands-on LLM systems: RAG, embeddings, tool calling, orchestration.
- Experience with OpenAI GPT, Hugging Face, etc.
- Experience evaluating LLM outputs and debugging failures (hallucinations, leakage).
- Proficiency in Python or other AI/ML languages.
- Strong problem-solving and attention to detail.
- Excellent communication to explain tech to non-technical stakeholders.
- Collaborative, team-oriented, adaptable to changing requirements.
- English proficiency - upper-intermediate or higher.
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