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Job Description

JOB PROFILE DESCRIPTION

Kainos is recognised as one of the UK’s leading AI and data businesses, with a decade-long track record of delivering impactful, production-grade AI solutions for clients across government, healthcare, defence, and commercial sectors. Kainos is at the forefront of AI innovation, trusted by Microsoft, AWS, and others to deliver advanced AI and data solutions at scale.

Our 150-strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government’s AI Cyber Security Code of Practice implementation guide and we partner with leading organisations to ensure AI is deployed ethically, securely and with measurable business value. Our teams are at the cutting edge of AI research, and delivery, it is truly an exciting team to join Kainos as we further grow our AI capability.

MAIN PURPOSE OF THE ROLE & RESPONSIBILITIES IN THE BUSINESS:

As a Senior AI Engineer at Kainos, you will deliver advanced AI solutions leveraging state-of-the-art machine learning, generative and agentic AI technologies. You will drive the adoption of modern AI frameworks, AIOps best practices and scalable cloud- architectures. Your role will involve hands-on technical delivery, collaborating with customers to translate business challenges into trustworthy AI solutions and ensuring responsible AI practices throughout. As a technical mentor, you will foster a culture of innovation, continuous learning, and engineering excellence.

It is a fast-paced environment, so it is important for you to make sound, reasoned decisions. You will do this whilst learning about new technologies and approaches, with talented colleagues that will help you to develop and grow. You will support your colleagues and more junior developers, providing direction support as you solve challenging problems together.

MINIMUM (ESSENTIAL) REQUIREMENTS:

A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Experience developing solutions at scale on cloud platforms (Azure & AWS), containerisation and orchestration tools such as Kubernetes and Docker. Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data. Understanding of responsible AI principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working.

DESIRABLE:

Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with AI security, privacy, and compliance standards e.g. ISO42001.

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