Job Summary :
We are seeking a highly skilled and creative AI Engineer with strong expertise in Generative AI, Large Language Models (LLMs), and Prompt Engineering. The role focuses on designing, developing, and optimizing intelligent AI-driven systems that enhance automation, improve user interactions, and deliver scalable business solutions.
The ideal candidate will have a deep understanding of transformer architectures, prompt design, and RAG (Retrieval-Augmented Generation) pipelines, with hands-on experience building and deploying models using platforms like OpenAI, Anthropic, Hugging Face, and Azure OpenAI.
Key Responsibilities :
- Design, test, and refine prompts to optimize performance of LLMs such as GPT-4, Claude, Gemini, and open-source models.
- Collaborate with cross-functional teams (product, design, engineering, marketing) to develop AI-driven features and tools.
- Conduct experiments and evaluate to test the accuracy, safety, and quality of AI-generated outputs, learning best practices along the way.
- Develop context-aware prompts, multi-turn dialogues, and dynamic prompt chaining for diverse applications.
- Build prompt libraries and templates for different business use cases (search, summarization, code generation, Q&A).
- Conduct A / B testing to assess model accuracy, creativity, factual reliability, and bias mitigation.
- Automate prompt workflows and integrate prompt chains with APIs and tool stacks.
- Fine-tune models or build retrieval-augmented generation (RAG) pipelines when needed.
- Stay curious and keep learning about the latest advancements in generative AI, NLP, and prompt engineering through hands-on practice and research
Required Skills & Qualifications :
Bachelor’s degree in computer science.2 years of experience working with LLMs, AI systems, NLP frameworks.Strong understanding of transformer models and training.Experience using OpenAI (ChatGPT, GPT API), Anthropic, Cohere, Hugging Face, or similar platforms.Strong proficiency in Python, with hands-on experience using leading AI frameworks and libraries such as LangChain, LlamaIndex, and others commonly used in LLM and NLP development.Familiarity with prompt tuning, zero-shot and few-shot learning, and LLM evaluation.Background in UX, technical writing, or content design is a plus.