326 to 350 of 842 Retrieval-Augmented Generation Jobs in the UK

from early foundations to a production-grade, self-service platform: Amazon Bedrock and the surrounding tooling (model access and routing, guardrails, knowledge bases/RAG patterns, agentic workflows), with the observability, cost controls and security posture required to run it in a regulated environment (AI Experience not essential but highly ...

from early foundations to a production-grade, self-service platform: Amazon Bedrock and the surrounding tooling (model access and routing, guardrails, knowledge bases/RAG patterns, agentic workflows), with the observability, cost controls and security posture required to run it in a regulated environment (AI Experience not essential but highly ...

system design, application development, testing, and operational stability. Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals, and coding assistants. Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production-grade ...

learn (or existing knowledge of) Spark. Familiarity with a core data or AI domain: modern data engineering, streaming, machine learning, or Generative AI (e.g. RAG, fine-tuning, LLMOps). Experience with the modern data stack and open-source data tooling, and with at least one major public cloud (AWS, Azure ...

Snowflake Platform including Cortex, Horizon and Snowpark. Advanced proficiency in Azure, AWS, or GCP platform setup and administration. Practical understanding of Generative AI, RAG frameworks, Agentic AI architectural patterns, and security guardrails. Solid understanding of data governance standards (lineage, access control) and performance/cost optimization frameworks. Job responsibilities Lead ...

Snowflake Platform including Cortex, Horizon and Snowpark. Advanced proficiency in Azure, AWS, or GCP platform setup and administration. Practical understanding of Generative AI, RAG frameworks, Agentic AI architectural patterns, and security guardrails. Solid understanding of data governance standards (lineage, access control) and performance/cost optimization frameworks. Job responsibilities Lead ...

exposure to AI or ML security in practice. Solid understanding of AI and LLM security concepts, including prompt injection, jailbreaks, data poisoning, model extraction, RAG manipulation, and agentic risks such as tool poisoning, excessive agency, and MCP server vulnerabilities. Experience securing agentic AI systems, including sandboxing, permission scoping, human ...

marketplace business with high-cardinality partner/catalogue data. Experience building or supporting AI/LLM-facing data products — a chatbot, a RAG pipeline, an agent with database access. Experience with GitHub Actions-based CI/CD for data pipelines. Good To Know: TodayTix Group takes care of our team. ...

largest enterprise customers and prospects unlock the full potential of the AI-powered Zendesk Resolution Platform. You will design and architect next-generation service solutions that drive measurable business outcomes, transforming traditional support centers into highly efficient, Autonomous Service Workforces. Simultaneously, you will act as a critical technical … Model (LLM) Literacy: Exposure to or hands‐on experience with experience architecting and deploying generative AI solutions, prompt engineering, Retrieval‐Augmented Generation (RAG) frameworks, and Agentic AI reasoning systems. Modern API & Integration Proficiency: Advanced expertise with RESTful APIs, JSON implementations, web services, database design ...

multi‐modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval‐Augmented Generation (RAG), APIs, and enterprise data integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability ...

design, model selection, prompt engineering, and responsible AI practices. You should be comfortable discussing topics ranging from model fine-tuning and RAG (Retrieval-Augmented Generation) architectures to AI governance, cost optimization for AI workloads, and emerging trends in generative AI. Your ability to translate ...

agentic AI workflows that automate and streamline complex business processes. Design and apply advanced techniques such as semantic search, retrieval‐augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation. Develop ...

platforms that support AI‐powered applications, machine learning workloads, or agentic systems. Experience with GCP AI services, vector databases, retrieval‐augmented generation (RAG), model operations, or AI governance frameworks. Experience operating in multi‐cloud environments and helping organisations establish consistent platform standards across cloud ...

enterprise, high‐bar engineering environment. Demonstrated experience designing, building, and deploying large language model applications, including prompt engineering, evaluation, retrieval‐augmented generation, and agent orchestration. Familiarity with modern generative AI components such as large language model APIs, vector stores, embeddings, tool and function calling ...

enterprise, high‐bar engineering environment. Demonstrated experience designing, building, and deploying large language model applications, including prompt engineering, evaluation, retrieval‐augmented generation, and agent orchestration. Familiarity with modern generative AI components such as large language model APIs, vector stores, embeddings, tool and function calling ...

assessment, alignment and misalignment analysis, adversarial testing, and red‐teaming Strong LLM and Generative AI engineering fluency, including prompting strategies, retrieval‐augmented generation, context and memory design, function and tool calling, guardrails, observability, and failure‐mode analysis Track record of taking advanced AI systems ...

architectures, including Kafka Agentic AI and ML Commercial and open‐source LLMs integrated into agentic workflows Tooling for agent orchestration, retrieval‐augmented generation, vector storage, and evaluation Schema validation and structured data handling AI-assisted development Use of AI-assisted and agentic development tools ...

data pipelines and platform components Experience of coaching and mentoring data engineers to achieve successful outcomes Familiarity with AI-focused data engineering, including RAG systems, vector databases, embedding pipelines, and semantic indexing A proven record of collaboration with colleagues and stakeholders Process mapping and supporting documentation production Test plan formulation ...

Migration of analytical/data science workloads (convert and migrate R development/Libraries to Databricks). AI/ML, LLM integration, model lifecycle, RAG/vector retrieval or model-serving experience. Large-scale enterprise platform transformation and regulated-industry experience. Strong cost optimisation and FinOps delivery experience ...

paths, failure handling, and responsible AI practices. Experience defining AI evaluation frameworks and using interaction data, testing, and analytics to improve performance. Knowledge of RAG, semantic search, enterprise knowledge systems, grounding, observability, and regression testing. Working knowledge of APIs, cloud services, software architecture, integration patterns, and modern engineering practices. Ability ...

Experience delivering AI solutions within Healthcare or Life Sciences Strong Python and modern AI framework expertise Hands-on experience with LLMs, Generative AI, RAG and AI agents Knowledge of Azure, AWS or GCP Experience taking AI solutions from concept into production Understanding of sensitive data, security, governance and responsible ...

Spark, Iceberg, Kafka, dbt, Scikit-Learn, XGBoost, PyTorch, MLFlow, GraphFrames, Ray, AWS S3, EMR, SageMaker, Lakeformation, Terraform, Docker, GitHub CI/CD, Knowledge Graphs, RAG, graph ML, probabilistic programming, A/B testing. Условия No conditions specified #J-18808-Ljbffr ...

mandatory) tailored to complex banking environments. AI-Native Engineering & Agentic Workflows: Pioneer the integration of AI-native architecture patterns-including agentic workflows, autonomous systems, RAG pipelines, and model-driven orchestration-into core banking, payments, and risk operations. Domain Modernization & Composable Banking: Translate complex business requirements across retail banking, corporate banking ...

Salesforce Financial Services Cloud | Snowflake | ComplyAdvantage | OCS | SQL | Python | REST APIs | Event-Driven Architecture | Cloud | CI/CD | DevSecOps | AI/ML | GenAI | LLMs | RAG | Data Governance | Data Lineage If you have the above experience please apply immediately ...

Salesforce Financial Services Cloud | Snowflake | ComplyAdvantage | OCS | SQL | Python | REST APIs | Event-Driven Architecture | Cloud | CI/CD | DevSecOps | AI/ML | GenAI | LLMs | RAG | Data Governance | Data Lineage If you have the above experience please apply immediately ... ...