351 to 375 of 695 Artificial Intelligence Engineering Jobs in England

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 ...

Rentokil Initial is seeking a pragmatic, highly technical AI Engineering Lead to head the Agentic Factory within the Group AI Team. You will bridge business needs and technical execution, delivering production‐grade multi‐agent AI systems and scalable pipelines. You will mentor engineers, partner with Data Platform ...

technical leadership, engaging with clients, and shaping high-level designs to deliver critical business outcomes. The ideal candidate will have strong experience in AI engineering and data platforms, including Databricks and Azure services, along with excellent communication skills and the ability to influence C-level clients. #J ...

phase and requires an experienced AI professional to join their head office team. This role is a rare opportunity to combine hands‐on AI engineering expertise with client consulting, solution delivery, and technical leadership. You’ll play a critical role in shaping solutions for high‐profile organisations across ...

delivering AI-native, cloud-smart solutions for high-impact clients. You don’t just shape strategy—you bring it to life through engineering-first thinking and relentless problem-solving. Your mission: Partner with visionary clients. Translate complexity into clarity. Deliver intelligent outcomes that scale. Here … models into outcomes. ‘Three sentence prompt’ with double quotes is not really a prompt. It's a search. Modern Tech Consultant DNA: Applied AI Engineering, Cloud Engineering, Data Intelligence, Work Modernization, Process modernization — not just the buzzwords, but the real understanding of how these offerings ...

build automated and semi-automated evaluation frameworks, and validate both deterministic software behavior and non-deterministic AI outputs. This role works closely with AI Engineering, Product, Operations, Engineering, business analysts, business owners, and subject matter experts to build quality into AI products from the start … including test coverage, pass rates, defect density, escaped-defect rate, AI accuracy metrics, hallucination rate, evaluation-score trends, and release readiness Partner with AI Engineering to embed testing, monitoring, observability, evaluation, and quality controls into the AI development lifecycle Conduct safety, bias, adversarial, and red-team testing ...

enabled financial crime framework at the forefront of FinTech innovation. Youll work closely with the senior leadership team, and cross-functional teams-including AI, engineering, and product-to embed scalable controls that strengthen trust, meet regulatory standards, and enhance customer experience. What Youll Do: Lead the 1st Line ...