Lead AI Engineer

Kainos

. Architect, design, and deliver advanced AI solutions using state-of-the-art machine learning, generative AI, and agentic AI technologies .

Posted 11/11/2026full-timeRemote • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and delivering advanced AI solutions, with a strong focus on responsible AI practices and scalable cloud-native architectures. Proven ability to lead technical teams, mentor colleagues, and translate complex business challenges into effective AI strategies.

Highest-signal resume keywords

AI Solution ArchitecturePython ProgrammingMachine Learning DeploymentCloud Platforms (Azure, AWS)Deep Learning Frameworks (PyTorch, TensorFlow)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningGenerative AIPrompt EngineeringModel EvaluationData EngineeringCI/CDContainerizationOrchestration (Kubernetes, Docker)Fine-Tuning LLMsMachine Learning Libraries (scikit-learn, XGBoost)

Soft Skills

Interpersonal SkillsLeadershipMentoringCollaborationProblem-Solving

Tools & Technologies

AzureAWSKubernetesDockerVector DatabasesSemantic SearchKnowledge Graphs

Industry Keywords

Responsible AIAI SecurityPrivacy StandardsCompliance StandardsOpen-Source Contributions

Tech Stack

Tools & technologies

AWSAzureCloudDockerKubernetesPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Architect, design, and deliver advanced AI solutions using state-of-the-art machine learning, generative AI, and agentic AI technologies
Drive adoption of modern AI frameworks, AI Ops best practices, and scalable cloud-native architectures
Provide hands-on technical leadership
Collaborate with customers to translate business challenges into trustworthy AI solutions
Ensure responsible AI practices throughout solution delivery
Mentor technical colleagues and foster innovation, continuous learning, and engineering excellence
Manage, coach, and develop a small number of staff
Manage employee performance and assist with career development
Provide direction and leadership for the team while solving challenging problems

Requirements

What you’ll need

Minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics, or a similar quantitative field
Demonstrable experience deploying modern AI/ML solutions into production
Experience with prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics such as precision, recall, NDCG, and drift detection
Strong Python skills and grounding in software engineering best practices, including CI/CD, testing, and code reviews
Experience developing solutions at scale on Azure and AWS
Experience with containerisation and orchestration tools such as Kubernetes and Docker
Expertise in data engineering for AI, including large-scale, unstructured, and multimodal data
Understanding of responsible AI principles, model interpretability, and ethical considerations
Strong interpersonal skills and ability to lead client projects and establish requirements in non-technical language
Experience managing, coaching, and developing junior team and community members
Demonstrable experience with modern deep learning frameworks such as PyTorch and TensorFlow
Experience with fine-tuning or distillation of LLMs such as GPT, Llama, Claude, and Gemini
Experience with machine learning libraries such as scikit-learn and 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 such as ISO 42001

Benefits

Comp & perks

People-first culture with supported professional growth
Recruitment accommodations and adjustments available
Recruitment process tailored to individual needs through private conversation