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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading AI strategy implementation, designing scalable AI and machine learning solutions, and establishing best practices for AI engineering. Proficient in mentoring technical teams and ensuring compliance with security and regulatory standards.
Highest-signal resume keywords
AI Strategy ImplementationGenerative AI SolutionsAzure AI ServicesLarge Language ModelsMLOps Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
PythonAI Engineering StandardsMachine Learning SolutionsData Engineering ConceptsAPIsMicroservicesCloud-Native ArchitectureModel Evaluation MethodologiesPrompt EngineeringRetrieval-Augmented Generation
Soft Skills
MentoringTechnical Decision-MakingStakeholder Influence
Tools & Technologies
Microsoft CopilotAzure OpenAIAWS AIGoogle Vertex AILangChainSemantic Kernel
Certifications & Qualifications
Relevant Cloud CertificationsSecurity Clearance (SC)
Industry Keywords
Responsible AI PrinciplesAI GovernanceCompliance RequirementsAgile DeliveryCI/CD Practices
Tech Stack
Tools & technologiesAWSAzureCloudMicroservicesPython
About the role
Key responsibilities & impact- Lead the technical implementation of the organisation's AI strategy
- Evaluate emerging AI technologies and identify adoption opportunities
- Define AI engineering standards, patterns and best practices
- Act as technical authority for AI-related projects and programmes
- Mentor and develop engineers, architects and technical specialists
- Design scalable AI and machine learning solutions
- Define architectures for Generative AI, Machine Learning and Intelligent Automation platforms
- Establish patterns for integrating AI services into enterprise applications
- Ensure solutions align with enterprise architecture, security and compliance requirements
- Lead technical design reviews and architecture governance activities
- Build and oversee development of AI-powered applications and services
- Lead proof-of-concepts, pilots and production implementations
- Collaborate with Agile delivery teams to embed AI capabilities into products and services
- Establish CI/CD pipelines and MLOps practices
- Drive technical quality, performance and operational resilience
- Design and implement Large Language Model solutions and Retrieval-Augmented Generation architectures
- Implement prompt engineering and AI orchestration frameworks
- Evaluate AI model performance, accuracy and cost optimisation
- Use Microsoft Copilot, Azure OpenAI and other enterprise AI services where appropriate
- Embed responsible AI principles and implement monitoring, auditability and model governance controls
- Assess risks relating to bias, security, privacy and ethical AI use
- Work with legal, security and compliance teams to maintain regulatory adherence
- Support AI governance boards and decision-making forums
- Engage senior business stakeholders, translate requirements into technical solutions, present AI roadmaps and recommendations, and build relationships across technology, data and operational teams
Requirements
What you’ll need- Strong software engineering background
- Experience delivering AI, machine learning or Generative AI solutions
- Knowledge of Azure AI Services, Azure OpenAI, AWS AI or Google Vertex AI
- Experience with Python and modern development frameworks
- Strong understanding of APIs, microservices and cloud-native architecture
- Experience with data platforms, databases and data engineering concepts
- Knowledge of MLOps, DevOps and CI/CD practices
- Hands-on experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, and AI orchestration frameworks such as LangChain or Semantic Kernel
- Understanding of model evaluation methodologies
- Knowledge of responsible AI principles
- Demonstrable experience leading technical teams
- Ability to coach and mentor engineers
- Strong technical decision-making skills
- Experience influencing stakeholders at multiple organisational levels
- Relevant cloud certifications (Microsoft Azure preferred)
- Security Clearance (SC) required before commencing employment
- Generally, eligibility for full SC requires residence in the UK for the last 5 years; in some circumstances, 3 years' UK residence over the last 5 years may be accepted with additional overseas checks
- Degree in Computer Science, Software Engineering, Data Science or related discipline, or equivalent experience
Benefits
Comp & perks- Private medical insurance
- Buying or selling annual leave
- Cycle to work schemes
- Employee discounts
- Paid volunteering day
- Stocks and shares
- Annual bonus
- Employee networks
- Wellbeing policies
- Inclusive features