Prompt Engineer

You will be part of our AI enablement services team which is tasked with helping SME's leverage the use of generative artifical intelligence. We do this by implementing complex prompt artchitectures along with fine tuning of open source LLMs to create highly specific customised LLMs that can be delivered to businesses in a secure and complian manner.

As a Prompt Engineer at Noesis, you will play a vital role in shaping the performance of our AI models and ensuring they deliver exceptional results for our clients. You will have the exciting opportunity to work closely with our cross-functional teams, including Research & Development, Product, and Customer Success, to understand customer workflows, design prompts, and fine-tune LLMs for specific use cases.

Your expertise in leveraging embeddings for RAG-based workflows will be key in driving innovation and delivering impactful solutions.

Responsibilities:

Research and Experimentation: Conduct personal research and experimentation to stay up-to-date with the latest developments in AI and language models. Explore and implement novel approaches to prompt engineering to enhance the capabilities of our models.

Prompt Design and Optimization: Design and fine-tune prompts for GPTs on our proprietary platform, Brainstormer.io. Understand customer workflows and utilize your expertise to create prompts that align with their requirements and yield superior results.

Language Model Fine-tuning (LLM): Leverage your understanding of fine-tuning techniques to optimize LLMs for specific use cases. Refine models and improve their performance across various domains.

Embeddings for RAG Workflows: Effectively use embeddings to enhance RAG-based workflows. Develop strategies to leverage embeddings for better information retrieval and generation within the context of our AI models.

Collaboration and Communication: Collaborate closely with the Research & Development, Product, and Customer Success teams to understand customer needs, provide prompt engineering expertise, and contribute to the overall success of our AI solutions.

Requirements:

Expertise in Prompt Engineering: Proven experience and expertise in prompt engineering techniques, with a strong understanding of the AI and language model landscape.

Familiarity with AI Developments: In-depth knowledge of the latest advancements in the AI and language model space, including recent research papers, methodologies, and best practices.

Strong Problem-Solving Skills: Ability to analyze complex problems, develop innovative solutions, and optimize prompts and models for improved performance.

Experience in LLM Fine-tuning: Prior experience in fine-tuning language models for specific use cases, be it through domain adaptation or transfer learning, is highly valued.

Understanding of Embeddings and RAG Workflows: Knowledge and practical experience in leveraging embeddings for RAG-based workflows, improving information retrieval, and generation in AI models.

Collaborative Mindset: Strong teamwork and communication skills, with the ability to collaborate effectively with cross-functional teams and contribute to a collaborative work environment.

Degree in Computer Science or a related field