Generative AI Engineer

Role: Generative AI Engineer

Location: Hybrid Working

Rate: Up to £750 per day (Inside IR35) dep on exp

Length: 6 months+

Consultant: Thomas Peters, email (see below)

Our client, an advisory business, is seeking an experienced Generative AI Engineer (Tech Squad Member) to support the industrialisation of the tools developed during the programme.

In this role, you will be involved in the development and deployment of generative AI models and solutions, supporting key projects, and driving impactful AI initiatives. You'll work closely with senior AI professionals and contribute to designing and implementing AI solutions that deliver real business value.

AI Solution Development:

• Assist in the design and development of generative AI models and solutions across various Watts projects.
• Work with senior engineers to implement AI models into business processes, ensuring the solutions align the businesses' needs and objectives.

Coding & Implementation:

• Write, optimize, and implement AI code for model development, integrating generative AI models into scalable production environments.
• Use tools such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake to build and deploy AI solutions.
• Collaborate with other engineers on coding best practices, version control, and continuous integration/continuous delivery (CI/CD) processes.

Data Governance & Security

• Ensure compliance with KPMG's data governance policies and industry regulations regarding AI models and data processing.
• Implement best practices in data privacy, security, and ethical AI, particularly when handling sensitive data.

Skills:

• Proficient in coding and optimizing generative AI models, particularly in the areas of prompt engineering and LLMs.
• Familiarity with AI/ML algorithms and model deployment in cloud environments.
• Experience with version control tools (eg, Git), and knowledge of Docker and containerization.
• Strong communication and collaboration skills, with the ability to work effectively in cross functional teams.

Educational Background:

• BSc in Computer Science, Statistics, Engineering, or related field
• Advanced certifications in AI/ML, cloud computing, or data engineering are advantageous.