Lead Consultant
2 days ago
Penarth
We are looking for an AI Engineer with strong expertise in Artificial Intelligence, Machine Learning, Generative AI, Google Cloud and AI-powered User Experience (UX) to design, develop and deliver scalable enterprise AI solutions. The role combines hands-on AI/ML engineering with AI/UX design, working closely with Data Scientists, ML Engineers, UX Designers, Product Managers, Cloud Architects and business stakeholders to build intelligent, user-centric and enterprise-ready solutions. • AI/ML Engineering & Solution Development Design, develop and support scalable and optimised AI/ML solutions for enterprise use cases., • Develop and implement AI/ML algorithms and solutions based on business and user requirements., • Build data processing workflows for extracting, transforming and loading large volumes of structured and unstructured data., • Prepare, integrate and transform data required for AI/ML model development and deployment., • Work with Data Scientists and ML Engineers to convert analytical and theoretical models into production-ready AI solutions., • Conduct experiments to evaluate model performance, accuracy, scalability and reliability., • Identify, troubleshoot and resolve issues affecting deployed AI/ML solutions., • Apply statistics, scripting and programming skills to develop and optimise AI solutions., • Work with relevant software platforms and cloud environments where AI/ML models are developed and deployed., • Google Cloud AI & Generative AI Design and deliver AI solutions using Google Cloud AI services, including Vertex AI and managed ML services., • Develop enterprise use cases using Generative AI, LLMs, foundation models, embeddings and conversational AI., • Design AI/ML pipelines covering data ingestion, processing, model development, testing, deployment and monitoring., • Work with BigQuery, data pipelines and Google Cloud analytics services to support AI/ML workflows., • Integrate Google AI APIs for use cases including Natural Language, Vision, Speech, Search and Recommendations., • Evaluate and experiment with emerging Google AI capabilities and translate them into practical enterprise solutions., • Balance custom AI/ML development with managed Google Cloud services based on performance, scalability, cost and business requirements., • MLOps & Model Lifecycle Support model training, validation, deployment, monitoring and lifecycle management., • Implement appropriate MLOps practices for model versioning, deployment and monitoring., • Monitor deployed models and identify opportunities for performance optimisation., • Support continuous improvement of AI/ML solutions based on model performance and user feedback., • Ensure AI solutions are scalable, reliable and suitable for enterprise production environments., • AI/UX & User Experience Design AI-powered experiences that translate complex AI capabilities and model outputs into intuitive user interactions., • Work with UX teams to integrate AI capabilities across web, mobile, conversational interfaces, dashboards and enterprise applications., • Design interfaces that allow users to understand, validate and act on AI-generated insights., • Develop explainable and transparent AI experiences that improve user trust and adoption., • Design human-in-the-loop workflows where users can review, challenge and provide feedback on AI outputs., • Contribute to user research, journey mapping, prototyping and usability testing for AI-powered products. Translate user needs and business requirements into practical AI solution designs., • Data, Analytics & AI Insights Work with Data Scientists, Data Engineers and Analytics teams to prepare and utilise data for AI solutions., • Analyse complex datasets and AI outputs to identify actionable business insights., • Define and track AI solution KPIs including model performance, adoption, accuracy, user engagement and business impact., • Support experimentation and A/B testing to evaluate AI features and user experiences., • Assess data quality, bias and representativeness to support reliable AI outcomes., • Responsible AI & Governance Apply responsible AI principles throughout the design and development lifecycle., • Identify and address risks relating to bias, fairness, privacy, security, transparency and explainability., • Support responsible use of enterprise data in AI/ML solutions., • Ensure AI solutions align with applicable data protection, security and regulatory requirements., • Promote transparent and human-centred AI design practices., • Stakeholder & Client Collaboration Collaborate with Product Managers, UX Designers, Data Scientists, Data Engineers, Cloud Architects and business stakeholders., • Translate business requirements into technical AI/ML solutions and user-centric experiences., • Lead technical discussions, AI solution workshops and design-thinking sessions with stakeholders., • Communicate AI concepts, model outputs and technical considerations to both technical and non-technical audiences., • Support client engagements, solution proposals, proof-of-concepts and AI transformation initiatives., • Bachelor's in Computer Science, Information Technology, AI/ML or related fields., • 3+ years of professional experience in AI/ML engineering, AI solution development or related AI engineering roles., • Strong hands-on experience developing and deploying AI/ML solutions., • Experience with data extraction, transformation, integration and processing for AI/ML applications., • Strong programming/scripting skills in Python or equivalent programming languages., • Strong understanding of machine learning, statistics, algorithms and model evaluation., • Experience working with Generative AI, LLMs, embeddings and conversational AI., • Hands-on experience with Google Cloud AI / Vertex AI or comparable enterprise AI/ML platforms., • Experience with BigQuery, cloud data pipelines and analytics platforms., • Understanding of MLOps, including model training, deployment, monitoring, versioning and lifecycle management., • Experience troubleshooting and optimising deployed AI/ML models., • Experience designing or contributing to AI-powered UX and enterprise digital experiences., • Knowledge of UX principles, user research, prototyping and human-centred design is highly desirable., • Experience with Figma or similar UX/prototyping tools is an advantage., • Strong understanding of responsible AI, explainability, data privacy and AI governance., • Excellent communication, stakeholder management and presentation skills., • Experience working in Agile, Design Thinking or cross-functional product development environments. #J-18808-Ljbffr