201 to 225 of 315 Artificial Intelligence Engineering Jobs in the UK excluding London

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 ...

drive advanced ML use cases across the firm, reporting to the AI Platform Owner. You will build scalable architectures, mentor a global AI engineering team, manage external providers, and ensure delivery aligned with business outcomes and industry best practices. A strong background in ML, data analysis, and software ...

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 ...

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 ...

Strategy? Have a passion for Architecture? Want to work in a team that is pushing the forefront of the latest technology in the Engineering and AI space? We can offer you this. Slalom is agnostic when it comes to the technology we work with and we support clients … Certified Developer - Associate Experience withstreaming data architecturesand real-time analytics Familiaritywithdata platformssuch asSnowflake, Databricks is a bonus Experience with ML/AI engineering, including building or integrating production-grade machine learning or generative AI solutions. Experience with agentic development patterns, including tool use, workflow orchestration, and evaluation ...

client delivery teams, responsible for designing, building, and operating production-grade agentic AI systems on AWS. This role sits at the intersection of AI engineering and cloud architecture, owning the end-to-end implementation of multi-agent pipelines, knowledge bases, and orchestration frameworks using Amazon Bedrock … observability and tracing tooling — CloudWatch, spans, and traces — to support debugging, performance monitoring, and compliance requirements Integrate LLMs into client applications through prompt engineering, context management, and function/tool calling patterns Leverage serverless infrastructure — AWS Lambda, DynamoDB, S3 — to build scalable, cost-efficient backends for AI workloads ...

Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives. Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs. Mentor and guide … machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker ...