1 to 25 of 88 Permanent Amazon Bedrock Jobs

building, and scaling enterprise-grade agentic AI architecture on AWS. This role focuses on establishing frameworks, patterns, and guardrails that enable safe, reliable, and cost-efficient AI solutions, leveraging Amazon Bedrock (Agents, Knowledge Bases, Guardrails, Flows) and Claude models. You will collaborate with cross-functional teams in product, engineering, data, and security to deliver next-generation AI capabilities … Define and evolve the enterprise agentic AI architecture, establishing reusable frameworks and standards for RAG, tool/function calling, and multi-agent orchestration. Design and implement AI solutions using Amazon Bedrock and integrate with core AWS services (Lambda, Step Functions, EventBridge, ECS/EKS, S3, Aurora, OpenSearch, DynamoDB). Drive adoption of agentic AI patterns - planning, memory, and … human-in-the-loop - ensuring alignment with enterprise security and compliance frameworks. Guide model selection and optimization (Claude family and Bedrock models), including prompt schema design, adapters, and fine-tuning strategies. Implement advanced RAG pipelines with optimized chunking, reranking, grounding, and hybrid/vector retrieval using OpenSearch and pgvector. Apply Guardrails and data-governance controls (IAM/ABAC, KMS More ❯

Sound understanding of GenAI solution constructs e.g., LLMs, RAG, Guardrails, MLOps and multi-modality 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! Experience in legacy environments and More ❯

. Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal More ❯

. Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal More ❯

. Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal More ❯

. Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal More ❯

. Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid-level to Principal More ❯

insights and generate solutions from structured and unstructured data. 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 ❯

insights and generate solutions from structured and unstructured data. 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 ❯

insights and generate solutions from structured and unstructured data. 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 ❯

insights and generate solutions from structured and unstructured data. 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 ❯

insights and generate solutions from structured and unstructured data. 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 ❯

OWASP Top 10 and a proactive approach to identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. Excellent communication and collaboration skills to More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯

ML algorithms or technologies using Python 2 years of experience with Retrieval Augmented Generation (RAG) Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant More ❯