Role Overview:

We are seeking highly skilled Prompt Engineers with strong expertise in Large Language Models (LLMs), prompt design, and advanced NLP solutions. The ideal candidate will have hands-on experience delivering LLM production projects, including prompt optimization, fine-tuning, retrieval-augmented generation (RAG), and secure deployment of LLM-based workflows in enterprise environments.

Key Responsibilities:

Design, test, and deploy prompts for real-world LLM applications ensuring consistency, relevance, and accuracy.
Develop prompt engineering pipelines integrating Python, LLM APIs, and data manipulation tools (e.g., Pandas).
Implement fine-tuning or RAG pipelines to optimize performance for enterprise use cases.
Define evaluation strategies using BLEU, ROUGE, semantic similarity, and human-in-the-loop validation frameworks.
Ensure compliance with security best practices (prompt injection prevention, safe output structuring, API limitations).
Collaborate with business and technical stakeholders to translate complex requirements into actionable LLM solutions.
Analyze outputs for consistency, scalability, and high-level architectural alignment.
(Good to Have) Work with vector databases and integrate with tools such as LangChain, LlamaIndex, OCR/NLP pipelines.

Mandatory Skills:

Prompt Engineering Experience: Proven track record of 2+ production-grade LLM projects.
Prompt Design Expertise: Deep understanding of prompt structures and contextual framing.
Python Proficiency: Strong Python development background with LLM API integration.
Advanced LLM Techniques: At least one fine-tuning or RAG pipeline implementation.
Evaluation & Validation: Familiarity with evaluation metrics (BLEU, ROUGE, semantic similarity).
Security Awareness: Knowledge of prompt injection, output filtering, API limitations.
Communication Skills: Strong ability to communicate technical and functional requirements.
Analytical Thinking: Balance of strategic design and output-level accuracy.

KBC Technologies Group

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Prompt Engineer