Python Developer - Generative AI

Description :

Python / GenAI / DI Developer Job Description.

Position Overview :

We are seeking a group of highly skilled and experienced Gen AI specialists to join our dynamic Gen AI COE.

The ideal candidates will have a strong background in designing and implementing AI solutions ideally using AWS technology.

This role requires a deep understanding of generative AI techniques, however we are aware that some of the technology we are dealing with is cutting edge and no-one will have long-lived experience.

We have a GraphRAG platform and we wish to start building team of people who know how to deploy, customise and extend the solution.

These people would eventually take on a wider range of responsibilities, within our COE, for example to work on Client projects.

The GraphRAG solution is however a good place to start and be a proving ground.

Key Responsibilities :

- Deploy solution into new customer tenant (based on a re-usable method).

- Onboard customer documents into the solution, including making sure diagrams have been properly parsed.

- Configure Langchain for vector processing and graph extraction.

- Create agents to generate new outputs from existing knowledge graph.

- Tune prompts so that customers can find the information they are looking for.

- Collaborate with on-shore teams who have customer relationships and share knowledge with other KANO developers around the world.

Required Skills and Qualifications :

- Technical data engineers with a strong desire and drive to learn new technologies, and to apply these technologies in new spaces.

- People with a real technical facility to solve problems without significant oversight or leadership.

- An understanding of AI, and AI ethics.

- An understanding of data safety in use of Large Language Models.

- Knowledge and experience of either AWS or Azure.

- AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2).

- Azure (azure Open AI service, Cosmos DB).

- Python.

Preferred Qualifications :

- Langgraph.

- Neo4j/cypher.

- AI RAG (retrieval augmented generation).

- Graph RAG.

- Few shot detection.

- Embedding models/LLMs how they work, how they are trained.

Aptitude :

- Dealing with ambiguity.

- Problem solving.

- Curiosity.