326 to 350 of 663 Artificial Intelligence Engineering Jobs in England

AI technologies, value clean, reliable solutions, and want to deliver practical, business-focused outcomes. Applicants may have a background in either Data or AI engineering, with a keen interest in driving value from data using modern AI and analytics techniques. Applicants must have experience leading project teams, providing … setting priorities, and ensuring high-quality delivery.Mentoring: Support and mentor junior team members within your workstream, sharing expertise and promoting best practices Data Engineering & Development: Design, build, and maintain scalable data pipelines, datasets, and data models to support analytics, reporting, and AI use cases.AI & Advanced Analytics: Develop ...

insights, and recommendations from both structured and unstructured data. As a Senior engineer, you will provide technical leadership, drive the adoption of modern AI engineering practices, and ensure that AI-powered solutions are robust, scalable, and reliable. Responsibilities Design, develop and maintain Python-based services and data processing … Contribute to the delivery of scalable AI-powered solutions that improve investigative processes through automation and intelligent insights. Help establish and promote modern AI engineering practices, including agentic workflows, prompt engineering and AI-assisted development. Essential Skills Strong Python development experience, including building production-grade services ...

insights, and recommendations from both structured and unstructured data. As a Senior engineer, you will provide technical leadership, drive the adoption of modern AI engineering practices, and ensure that AI-powered solutions are robust, scalable, and reliable. Responsibilities Design, develop and maintain Python-based services and data processing … Contribute to the delivery of scalable AI-powered solutions that improve investigative processes through automation and intelligent insights. Help establish and promote modern AI engineering practices, including agentic workflows, prompt engineering and AI-assisted development. Essential Skills Strong Python development experience, including building production-grade services ...

agentic delivery assets and accelerators Stay at the frontier of agentic tooling; new frameworks, model releases, platform updates Build your craft in production AI engineering within a supported, high-growth environment Experience Required Professional engineering experience with hands-on involvement in AI or agentic systems … Financial Services experience is a strong value add Set yourself apart Open source contributions to agentic or LLM tooling Personal projects demonstrating production AI engineering outside of employment Contact centre platform experience (e.g. Genesys, Sierra, Decagon, Parloa, PolyAI, NICE Cognigy, Agentforce Contact Centre and Amazon Connect) EU AI ...

work across teams to design modular, analytics-focused data workflows, model business logic, and deliver actionable insights. This hybrid role combines engineering rigor with analytical depth and business fluency, making it ideal for professionals who thrive at the intersection of data, technology, and strategy.The … ideal candidate is someone who:Has engineering foundations and enjoys building reliable, production-grade analytics solutions.Is comfortable working across data science, AI engineering, and DevOps responsibilities.Understands the principles of analytics development and applies software engineering standard methodologies (modularity, testing, version control) to data workflows.Demonstrates ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution … Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning ...

infrastructure. You will design test plans, execute cases, and build evaluation pipelines in a cross-functional environment. You will work with AI engineering, product, operations, and business stakeholders to embed testing, monitoring, and governance into the product lifecycle, supporting pilots, production rollouts, and post-release updates. #J ...

translate business challenges into practical technical solutions. Using tools such as GitHub Copilot, Claude and Cursor to accelerate software development. Maintaining strong engineering standards across testing, security, code … quality, CI/CD and production readiness. Building prototypes and proof-of-concepts that can be evolved into production solutions. Helping define reusable AI engineering patterns, components and accelerators. Evaluating emerging AI frameworks and identifying where they genuinely add value. Mentoring developers and helping AI-assisted development become ...

Lloyds Bank plc is seeking a Lead Engineer for Advanced AI Engineering to shape and deliver AI solutions across the Data & AI Unit within the CTO. You will bridge applied research and production delivery, building MVPs and guiding teams in GenAI and responsible AI practices. You will collaborate ...