AI Developer

1. Design, develop and implement AI and Machine Learning solutions
2. Build software features across enterprise applications and data platforms
3. Develop Generative AI solutions using LLMs, RAG architectures and prompt engineering techniques
4. Explore OpenAI APIs, Azure AI services and emerging AI technologies
5. Contribute to the design and development of Agentic AI systems
6. Collaborate with Data Scientists, Engineers and business stakeholders to deliver AI-driven outcomes
7. Build and integrate APIs and cloud-based services
8. Support model development, testing, deployment and performance monitoring
9. Participate in Agile delivery, sprint planning, code reviews and engineering best practices
10. Contribute to technical documentation, knowledge sharing and continuous improvement initiatives, 1. Join a dedicated AI function within a leading investment management organisation
11. Work on cutting-edge Generative AI and Machine Learning initiatives
12. Exposure to OpenAI, Azure AI and emerging AI technologies
13. Collaborative environment working alongside experienced engineers and data specialists
14. Clear opportunities for learning, development and career progression
15. Hybrid working model with flexibility built in

This role is ideal for individuals with a strong foundation in Artificial Intelligence, Machine Learning, Software Engineering, or Data Science who are looking to apply their technical skills in a real-world environment and contribute to the development of innovative AI solutions., 1. Degree in Computer Science, Artificial Intelligence, Engineering, Mathematics or a related discipline (2:1 or above)

2. Strong programming skills in Python and/or C#
3. Understanding of object-oriented development principles and software engineering best practices
4. Knowledge of machine learning concepts and frameworks including:
5. PyTorch
6. Scikit-Learn
7. NumPy
8. Pandas
9. XGBoost
10. NLTK
11. SQL skills with the ability to query and manipulate structured datasets
12. Understanding of REST APIs and API integration
13. Familiarity with Large Language Models (LLMs), Retrieval Augmented Generation (RAG) and Generative AI concepts
14. Experience with unit testing frameworks such as PyTest, NUnit or xUnit
15. Strong analytical and problem-solving skills

Desirable Experience:

1. Internship, placement year or commercial experience within AI, Machine Learning or Data Science
2. Exposure to Azure, AWS, GCP or Snowflake
3. Knowledge of Agentic AI frameworks and autonomous AI systems
4. Experience using Git and version control tools
5. Understanding of CI/CD principles and deployment pipelines
6. Personal projects, hackathons, GitHub contributions or evidence of self-directed learning