[Hiring] Senior AI Engineer @Kainos

Role 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 citizen scale.

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, AI Ops best practices, and scalable cloud-native architectures.
• Engage in hands-on technical delivery, collaborating with customers to translate business challenges into trustworthy AI solutions.
• Ensure responsible AI practices throughout.
• Act as a technical mentor, fostering a culture of innovation, continuous learning, and engineering excellence.
• Support colleagues and junior developers, providing direction and support as you solve challenging problems together.

Qualifications

• 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 generation (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.

Requirements

• 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.

Benefits

• Embracing diversity, equity, and inclusion.
• Support from a friendly talent acquisition team throughout the recruitment process.
• Accommodations or adjustments available upon request.