14 of 14 Amazon Bedrock Jobs in the UK excluding London

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 ❯

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 ❯

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 ❯

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 ❯

product managers, solution architects, and other engineers to design end-to-end LLM-powered experiences for internal and customer-facing applications. Utilize AWS services such as Lambda, Step Functions, Bedrock, S3, ECS/Fargate, DynamoDB, and API Gateway to support scalable, serverless infrastructure. Write production-grade Python code, following best practices in software design, testing, and documentation. Build robust … frameworks. Expert in Python (asyncio, FastAPI preferred). Hands-on experience building and deploying applications on AWS, particularly using Lambda, Fargate, S3, Step Functions, and DynamoDB. Familiarity with AWS Bedrock is a plus. Strong understanding of agentic patterns, prompt chaining, tool calling, and memory/state management in LLM applications. Solid experience with unit and integration testing, CI/ 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 ❯