Job Application

Identifying use cases for GenerativeAI

Collection and processing of data to be used as input into GenAI models

Integrating organisation data into pre-trained models using techniques such as Retrieval Augmented Generation (RAG) and fine tuning

Working with vector databases and vector embeddings

Model deployment, serving and ongoing monitoring(MLOps/LLMOps)

Building web applications and user interfaces to allow users to interact with models

Researching existing solutions in the market

Developing guidance and standards for deploying AI applications

Coaching and upskilling colleagues, and wider staff, in Generative AI and software engineering

What the AI Engineer Will Need:

5+ years professional experience in software engineering/data engineering/machine learning engineering or a similar role

Proficient in Python

Knowledge of AI and machine learning, with a focus on Generative AI and Large Language Models (LLMs)

Knowledge of how to integrate data into pre-trained Generative AI models using techniques such as Retrieval Augmented Generation (RAG) and fine tuning, using libraries such as Langchain, LlamaIndex and Hugging Face, or cloud based tools such as AWS Bedrock or Google Vertex AI

Knowledge and experience of Natural Language Processing (NLP) techniques such as text embeddings, and an understanding of how different data representations can affect model performance

Experience of working with vector databases eg Pinecone

Experience of building and deploying web applications using cloud technologies

Knowledge of modern software engineering best practices eg test-driven development, CI/CD, containerisation

Knowledge of MLOps/LLMOps, including model deployment, serving and monitoring

Experience of working in an Agile environment