1 to 25 of 59 Amazon Bedrock Jobs in England

data, and engineering teams to translate business outcomes into scalable, secure, and cost-optimised architectures on AWS, accelerating delivery of conversational AI products using Amazon Bedrock, agentic frameworks, and retrieval-augmented generation (RAG) patterns. Key responsibilities: Own the target-state architecture for GenAI products (voice and chat), including … multi-account strategy, landing zone alignment, network patterns, and environment segregation (dev/test/prod). Define reference architectures for Amazon Bedrock, model orchestration, RAG, tool/function calling, and agentic workflows (e.g., LangChain/LangGraph/CrewAI/Strands-style patterns) with clear guardrails. Design enterprise ...

architecture Build and optimize data pipelines supporting AI inference and feedback loops Develop backend services/APIs enabling response suggestion workflows Integrate LLM capabilities (Amazon Bedrock) for response generation and embeddings Enable continuous model tuning via: telemetry data quality scoring usage analytics Work with structured and unstructured data … experience in: Python/JVM-based backend development REST APIs/microservices Experience with cloud-native architectures on AWS Data & AI Hands-on with: Amazon Bedrock (or equivalent LLM platforms) data pipelines (batch + streaming) embeddings/retrieval architectures Experience using: Snowflake (data platform integration, CDC concepts) PostgreSQL ...

should demonstrate experience across: Enterprise and solution architecture within complex organisations Cloud-based AI/ML platforms including Azure OpenAI, Azure ML, AWS Bedrock, SageMaker, Google Vertex AI, Databricks, Snowflake, Dataiku or similar technologies Designing scalable and cost-optimised AI solutions using serverless, containerised and Kubernetes-based environments Generative ...

ensuring alignment with business objectives and delivering impactful outcomes • Understanding of various GenAI platform & middleware and how they fit in GenAI architecture e.g., AWS Bedrock, Google Vertex, Langchain or LlamaIndex • Able to understand & apply advanced prompt engineering methods and related concepts (RAG, context windows, memory) RAG is a must ...

development (React, HTML/CSS, Streamlit, Gradio) for building interactive demo interfaces around AI prototypes. Experience with cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI) for model hosting and API integration. Background in marketing technology, digital marketing, or consumer-facing product development. Experience working in embedded consulting ...

DOING ────────────────────────────── 🔧 Technical Architecture • Designing end-to-end LLM and RAG systems integrated into complex enterprise workflows • Deploying and optimising models on AWS Bedrock, Azure AI Foundry, and self-hosted GPU infrastructure (vLLM, SGLang, Ollama) • Building robust MLOps/LLMOps pipelines — CI/CD, model monitoring, evaluation frameworks, observability • Making ...

built for production, not the lab Own the full technical lifecycle: model selection, deployment, MLOps, evaluation, and monitoring Deploy across cloud platforms (AWS Bedrock, Azure AI Foundry, GCP) and self-hosted GPU infrastructure Implement observability, security guardrails, and responsible AI frameworks from day one Lead cross-functional engineering teams ...

work across varied client stacks. Experience with cloud AI services and MLOps/LLMOps (eg, Azure AI Foundry, AWS SageMaker and/or Bedrock). Strong software engineering practices: Python, APIs, containerisation, CI/CD, IaC, testing, observability and production support. Modern ML/GenAI approaches: feature engineering, model ...

Databricks Deploy and operate containerised services on Kubernetes using Terraform for infrastructure-as-code Own and scale vector search infrastructure (OpenSearch, Algolia, AWS Bedrock Knowledge Bases) and embedding pipelines Build and maintain CI/CD pipelines for inference services, retrievers, ingestion workflows, and RAG components Implement observability across ...

/CD) AI/ML Exposure (Key Requirement): Practical exposure to AI/ML, such as: Working with cloud-based AI services (e.g. AWS Bedrock or similar) Supporting AI-enabled data products or workflows Understanding of generative AI and prompt engineering concepts Exposure to ML pipelines or collaboration with ...

design, API stability, backward/forward compatibility, and developer experience Nice to have: Experience with multi-modal systems (video, audio, or image processing) AWS Bedrock, SageMaker, or similar managed AI services Observability frameworks for LLM systems (Langfuse, Arize, LangSmith) RAG pipelines, vector databases, or retrieval-augmented systems CI/ ...

Stack Python TensorFlow/PyTorch LLM frameworks (LangChain, LangGraph, or similar agentic AI tooling) AWS/Azure cloud platforms (including AI services such as Bedrock) Data engineering tools (e.g. AWS Glue or equivalent) NLP, embeddings, vector databases, RAG architectures MLOps tooling for model deployment and monitoring Experience with distributed ...

development through knowledge sharing, presentations, or published work. Technologies and Platforms Cloud AI services: Azure OpenAI Service, Azure AI Services, Azure Machine Learning, AWS Bedrock, AWS SageMaker, AWS Lambda, API Gateway Data platforms: Microsoft Fabric, Databricks, Snowflake, Azure Data Factory AI development and tooling: Copilot Studio, Power Platform, Cursor ...

design authority Comfortable working directly with senior client stakeholders Strong mentoring and coaching capability Experience with some of the following technologies or ecosystems: Amazon Bedrock and SageMaker Claude/Anthropic Azure AI Foundry or Azure OpenAI Databricks Vector databases and RAG architectures Agentic AI orchestration frameworks ...

enterprise environments. Knowledge of authentication, secrets management, network security, and model governance. Experience developing and deploying AWS services, including: EC2 EKS S3 SQS DynamoDB Bedrock AgentCore Desirable Skills Experience with Kong API Gateway, Kong Mesh, and Flux CD. RESTful API and microservices development. Terraform and GitOps workflows. Exposure ...

Gateway, EventBridge, SQS, Step Functions Databases: DynamoDB, PostgreSQL, Aurora, MongoDB Frontend: React, TypeScript, MUI DevOps: AWS CDK, Terraform, Docker, GitLab CI, CodePipeline AI: Amazon Bedrock, RAG, LLM integrations Skills Required Commercial software engineering experience Strong AWS cloud/serverless experience Strong backend development skills in TypeScript, Python ...

from selecting the right model architecture to ensuring robust CI/CD and MLOps pipelines. Deploy and optimise models using cloud services like AWS Bedrock and Azure AI Foundry, or self-host them on GPU/CPU hardware using tools like vLLM, SGLang, and Ollama. Implement frameworks and approaches ...

enterprise environments. Knowledge of authentication, secrets management, network security, and model governance. Experience developing and deploying AWS services, including: EC2 EKS S3 SQS DynamoDB Bedrock AgentCore Desirable Skills Experience with Kong API Gateway, Kong Mesh, and Flux CD. RESTful API and microservices development. Terraform and GitOps workflows. Exposure ...

/analytics environments Candidates must demonstrate some level of exposure to AI/ML, such as: Working with cloud-based AI services (e.g. AWS Bedrock or similar) Supporting AI-enabled data products or workflows Understanding of generative AI/prompt engineering concepts If your experience matches the above requirements ...

experience Exposure to APIs, Terraform and/or CI/CD practices AI Exposure Required: Experience with AI/ML technologies, such as AWS Bedrock, Generative AI, prompt engineering, AI-enabled data products, or collaboration with Data Science teams Desirable: Data lake implementation experience AWS AI services Public sector ...

exposure (e.g. Terraform, APIs, CI/CD beneficial) * Experience working in Business Intelligence/analytics environments * Working with cloud-based AI services (e.g. AWS Bedrock or similar) * Supporting AI-enabled data products or workflows * Understanding of generative AI/prompt engineering concepts * Exposure to ML pipelines or collaborating with ...

enterprise LLM applications Retrieval-Augmented Generation (RAG) architectures AI agents and workflow orchestration AI solution architecture and systems integration Azure OpenAI, AWS Bedrock, GCP Vertex AI, or similar platforms Enterprise AI governance, scalability, and deployment considerations AI-enabled automation and operational transformation Skills & Experience Experience delivering AI, data ...

business stakeholders to deliver secure, cost-effective AI solutions on AWS. Key Responsibilities Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models) Build and deploy RAG systems using vector databases and semantic search Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI … practices Required Skills & Experience 1+ year hands-on experience deploying GenAI/LLM applications into production Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS Strong Python development skills with modern AI/ML libraries Practical experience using at least one LLM API Solid understanding ...

Python ETL/ELT and data pipelines BI tools (Power BI or similar) AI/ML (Essential) Exposure to cloud AI services (e.g. AWS Bedrock or similar) Experience supporting AI-enabled data workflows or products Understanding of generative AI/prompt engineering Exposure to ML pipelines or working with ...

data warehousing, analytics or data platform development within BI environments. Clear, practical exposure to AI/ML, for example cloud AI services (e.g. AWS Bedrock) AI-enabled data products, generative AI concepts or ML pipelines. Experience delivering AWS-based data solutions, ideally in complex or regulated settings. Familiarity with ...