17 of 17 Permanent Amazon Bedrock Jobs in the UK excluding London

the right fit for Deloitte landscape and uses cases. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI More ❯

the right fit for Deloitte landscape and uses cases. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI More ❯

the right fit for Deloitte landscape and uses cases. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI More ❯

the right fit for Deloitte landscape and uses cases. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI More ❯

the right fit for Deloitte landscape and uses cases. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI More ❯

embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB) databases Strong More ❯

modern data science tools/platforms. Strong stakeholder engagement skills and the ability to simplify complex insights into strategic recommendations. Bonus Points For: Experience with AWS AI tools (SageMaker, Bedrock, Lambda). Familiarity with low/no-code platforms. Knowledge of ethical AI frameworks and responsible innovation practices. What Success Looks Like Scalable, high-impact data science solutions delivering More ❯

expertise in one or more of the following technology areas: NoSQL, such as DocumentDB/MongoDB RDF Graph database such as GraphDB ML/AI such as Sagemaker/Bedrock Search technologies such as SOLR or Opensearch/ElasticSearch Data pipeline engineering utilising cloud-based technologies (AWS) Write high quality clean, testable code, with a focus on incremental innovation. More ❯

Plan Free breakfast and beverages Requirements Proven experience in .NET Core/C# and modern web frameworks like Angular/TypeScript Hands-on experience with LLM APIs (OpenAI, Claude, Bedrock), LangChain, or RAG-based architectures Deep familiarity with API design, microservices, and cloud-first development (AWS, Azure, or GCP) Experience building systems with MongoDB, SQL, or vector databases like More ❯

Plan · Free breakfast and beverages Requirements Proven experience in .NET Core/C# and modern web frameworks like Angular/TypeScript Hands-on experience with LLM APIs (OpenAI, Claude, Bedrock), LangChain, or RAG-based architectures Deep familiarity with API design, microservices, and cloud-first development (AWS, Azure, or GCP) Experience building systems with MongoDB, SQL, or vector databases like More ❯

reasoning, memory modules, and RAG pipelines. Use frameworks like LangChain, LangGraph, CrewAI, and tools like Pinecone, FAISS. Optimize performance and ensure responsible AI practices. Deploy via cloud platforms (AWS Bedrock, Azure AI, Google Vertex). Build UIs (Streamlit, Gradio, React) and integrate APIs and databases. Preferred Skills Experience with multi-agent systems and ethical AI. Familiarity with advanced model More ❯

complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React; familiarity with microservices More ❯

technical lead Technical skills: JAVA, AWS, TDD/BDD Previous experience in Financial Services or Large entity Some other highly valued skills may include: Exposure to Gen AI technology (Bedrock) DevOps experience Python You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking More ❯

to hand yourself in front of a customer who have problems and work out viable solutions- AI or ML experience highly beneficial- Experience with any of the following: AWS Bedrock, Agent2Agent Protocol (A2A), or other agentic AI solutions beneficial If this sounds of interest, please apply for this role. More ❯

with front-end applications (e.g., React, Nuxt, Vue) Collaborate closely with product teams to translate functional requirements into technical solutions Cloud-Native Development: Design and deploy containerized services with Amazon EKS (Elastic Kubernetes Service), focusing on scalability, resilience, and service orchestration Build cloud-native applications using AWS services such as Lambda, API Gateway, DynamoDB, SQS, and EventBridge Develop robust … LLM Enablement: Collaborate with data scientists and ML engineers to integrate AI/LLM capabilities into applications Build and expose intelligent APIs that leverage models from OpenAI, Hugging Face, Bedrock, or custom-trained models Support the lifecycle of AI features-from experimentation and fine-tuning to deployment and monitoring Quality, Security & Scalability: Ensure applications follow best practices for security … applications Strong coding skills in Node.js and Python Solid experience with AWS application services (Lambda, API Gateway, Step Functions, DynamoDB, etc.) Production experience deploying and managing containerized services on Amazon EKS Proven ability to design and build modern, API-driven systems in a scalable resilient cloud-based platform Experience developing or integrating data processing systems (batch or streaming) and More ❯

with front-end applications (e.g., React, Nuxt, Vue) Collaborate closely with product teams to translate functional requirements into technical solutions Cloud-Native Development: Design and deploy containerized services with Amazon EKS (Elastic Kubernetes Service), focusing on scalability, resilience, and service orchestration Build cloud-native applications using AWS services such as Lambda, API Gateway, DynamoDB, SQS, and EventBridge Develop robust … LLM Enablement: Collaborate with data scientists and ML engineers to integrate AI/LLM capabilities into applications Build and expose intelligent APIs that leverage models from OpenAI, Hugging Face, Bedrock, or custom-trained models Support the lifecycle of AI features-from experimentation and fine-tuning to deployment and monitoring Quality, Security & Scalability: Ensure applications follow best practices for security … applications Strong coding skills in Node.js and Python Solid experience with AWS application services (Lambda, API Gateway, Step Functions, DynamoDB, etc.) Production experience deploying and managing containerized services on Amazon EKS Proven ability to design and build modern, API-driven systems in a scalable resilient cloud-based platform Experience developing or integrating data processing systems (batch or streaming) and More ❯

with RAG models, multi-agent systems & more Build robust AI evaluation & monitoring frameworks Mentor, lead & inspire technical team in delivering AI products Experience Required Proven GenAI solution deployment (AWS Bedrock or similar) Deep knowledge of RAG models & agent workflows Experience with GenAIOps, AI security, and responsible AI Leadership skills & a builder's mindset Built and Architected an AI product More ❯