1 to 25 of 59 Amazon Bedrock Jobs

Associate Cloud Consultant, Data AnaIytics, AWS Professional Services, Public Sector Job ID: Amazon Web Services, Inc. - A97 At Amazon Web Services (AWS), we're hiring highly technical Data Analytics consultants to collaborate with our customers and partners on key engagements. Our consultants will develop and deliver proof-of … travel in their contract. Key job responsibilities In this role, you will work with our partners, customers and focus on our AWS offerings such Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon SageMaker, Amazon Bedrock, Amazon Q, and Amazon … ideal candidate will have extensive experience with design, development and operations that leverages deep knowledge in the use of modern data services like DynamoDB, Amazon Kinesis, Apache Kafka, Apache Spark, Amazon Sagemaker, Amazon RDS, technologies and other industry data structures and standards. A day in the life More ❯

help them achieve business outcomes with AWS. Our projects are often unique, one-of-a-kind endeavors that no one has done before. At Amazon Web Services (AWS), we are helping large enterprises build AI solutions on the AWS Cloud. We apply predictive technology to large volumes of data … our customers. You will leverage the global scale, elasticity, automation, and high-availability features of the AWS platform. You will build customer solutions with Amazon SageMaker, Amazon Bedrock, Amazon Elastic Compute (EC2), Amazon Data Pipeline, Amazon S3, Glue, Amazon DynamoDB, Amazon Relational … Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, AWS Lake Formation, and other AWS services. You will collaborate across the whole AWS organization, with other consultants, customer teams, and partners on proof-of-concepts, workshops, and complex implementation projects. You will innovate and experiment to help More ❯

team this SA will join supports Air Force Information, Cyber, and Intelligence customers, Combatant Commands, and Navy. This is an excellent opportunity to join Amazon's truly innovative technical teams, while also developing your skills and furthering your career within one of the most innovative and progressive technology companies … anywhere. In this role, you will have the opportunity to help shape and deliver on a strategy to build broad use of Amazon's computing web services (e.g., Amazon Bedrock, Amazon SageMaker, Amazon S3, Amazon EC2, and AWS Lambda) directly with customers and our … security - Economic and business - RFP/Acquisition support; technical architecture; understanding market trends; cost benefit analysis - Advisory/Consulting experience with Defense Department customers Amazon aims to be the most customer centric company on earth. Amazon Web Services (AWS) provides a highly reliable, scalable, low-cost infrastructure platform More ❯

Are you passionate about creating resilient cloud systems that power mission-critical operations? Do you want to apply leading edge artificial intelligence technologies like Amazon Bedrock to challenging problems? Do you thrive on engineering and maintaining the largest cloud infrastructure for some of the world's most complex … environments? Amazon Web Services is seeking talented AWS Dedicated Cloud Engineers to join our Region Reliability Engineering & Automation (RRE&A) team. Our mission is to ensure the seamless operation of AWS's dedicated cloud regions through proactive reliability engineering, automation, and leading-edge solutions. We seek individuals who bring … solutions to reduce repetitive tasks, building systems that minimize manual intervention, reduce cognitive load, and allow for proactive issue resolution. Build with technologies like Amazon Bedrock to reimagine reliability engineering. - Enhance Regional Reliability: Expand regional coverage for AWS's critical services. - Deep Dive and Troubleshoot: Conduct deep dives More ❯

Are you passionate about creating resilient cloud systems that power mission-critical operations? Do you want to apply leading edge artificial intelligence technologies like Amazon Bedrock to challenging problems? Do you thrive on engineering and maintaining the largest cloud infrastructure for some of the world's most complex … environments? Amazon Web Services is seeking talented AWS Dedicated Cloud Engineers to join our Region Reliability Engineering & Automation (RRE&A) team. Our mission is to ensure the seamless operation of AWS's dedicated cloud regions through proactive reliability engineering, automation, and leading-edge solutions. We seek individuals who bring … solutions to reduce repetitive tasks, building systems that minimize manual intervention, reduce cognitive load, and allow for proactive issue resolution. Build with technologies like Amazon Bedrock to reimagine reliability engineering. - Enhance Regional Reliability: Expand regional coverage for AWS's critical services. - Deep Dive and Troubleshoot: Conduct deep dives More ❯

career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's … experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools - Experience … building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value More ❯

Generative AI Model and Distributed Training, APJ Job ID: Amazon Web Services Korea LLC Do you want to help define the future of Go to Market (GTM) of Machine Learning and Generative AI (GenAI) at AWS? Would you like to join one of the fastest-growing organizations focused on … potential and challenges of GenAI models and applications to engineering teams and C-Level executives. This requires deep familiarity across the stack - compute infrastructure (Amazon EC2, Amazon EKA), ML frameworks PyTorch, JAX, orchestration layers Kubernetes and Slurm, parallel computing (NCCL, MPI), MLOPs, through to Amazon SageMaker Hyperpod … Amazon Bedrock as well as target use cases in the cloud. This is an opportunity to be at the forefront of technological transformations, as a key technical leader. Additionally, you will work with the AWS Generative AI and EC2 product teams to shape product vision and prioritize features More ❯

the best model for each individual legal use case. This approach includes working with large language models like Anthropic's Claude 2, hosted on Amazon Bedrock from Amazon Web Services (AWS), and OpenAI's GPT-4 and ChatGPT, hosted on Microsoft Azure. ACCOUNTABILITIES • Solve some of the More ❯

career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's … building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools. Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker. Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non More ❯

Engineers focusing on their growth and execution excellence. Lead and be responsible for on-time, great-quality project deliveries Developing MLOps pipelines leveraging the Amazon SageMaker platform and its features Developing Generative AI solutions and POCs, utilizing the latest architectures and technologies Delivering end-to-end ML products - model … data scientists and experience with software development and test automation Experience with one or more large language models, such as frameworks like OpenAI SDK, Amazon Bedrock, LangChain, and LlamaIndex Experience with Docker and Kubernetes Fluent written and verbal communication skills in English Working knowledge of some Vector Databases More ❯

with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production More ❯

with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production More ❯

with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production More ❯

functional teams, including data scientists, software engineers, and designers. Develop and implement state-of-the-art GenAI services leveraging Azure OpenAI models and AWS Bedrock service. Required Qualifications, Capabilities, and Skills: Formal training or certification in software engineering concepts with proficient applied experience. Strong hands-on experience with at More ❯

Engineering, Computer Engineering or related field. Experience in containerization - Docker/Kubernetes. Experience in AWS cloud and services (S3, Lambda, Aurora, ECS, EKS, SageMaker, Bedrock, Athena, Secrets Manager, Certificate Manager etc.) Proven DevOps/MLOps experience provisioning and maintaining infrastructure leveraging some of the following: Terraform, Ansible, AWS CDK More ❯

complex challenges, devise practical solutions, and iterate quickly based on feedback or data. Hands-on experience with cloud platforms, including AWS (e.g., EC2, Sagemaker, Bedrock, S3, Lambda), Google Cloud (e.g., Compute Engine, Vertex, GKE, BigQuery), Azure (e.g., Virtual Machines, Azure OpenAI) etc. Proficiency in scripting or programming (e.g., Python More ❯

complex challenges, devise practical solutions, and iterate quickly based on feedback or data. Hands-on experience with cloud platforms, including AWS (e.g., EC2, Sagemaker, Bedrock, S3, Lambda), Google Cloud (e.g., Compute Engine, Vertex, GKE, BigQuery), Azure (e.g., Virtual Machines, Azure OpenAI) etc. Proficiency in scripting or programming (e.g., Python More ❯

Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation More ❯

Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation More ❯

programming challenge during the interview process. Experience with Jupyter Notebooks, Python Data Science Libraries. Experience with ML-OPS and related tools (e.g., MLFLOW, Sagemaker, Bedrock) and ability to build interactive, insightful dashboards for monitoring ML models. Place of Performance: Hybrid work in San Antonio, TX. Desired Skills (Optional) Experience More ❯

of leading the architecture of multiple LLM and Generative AI solutions. Expertise in LLM ecosystems, including platforms like Azure OpenAI, Google Vertex, and AWS Bedrock, and mastery of relevant tech stacks. Proficient in cloud platforms (AWS, Azure, GCP) with experience in deploying and leading complex AI/ML workloads. More ❯

should be able to show strong capability in their core areas: Cloud Data Platforms Azure Synapse Analytics, Microsoft Fabric, Azure Data Lake, Azure SQL Amazon Redshift, AWS Athena, AWS Glue Google BigQuery, Google Cloud Storage, Dataproc Artificial Intelligence & Machine Learning Azure OpenAI, Azure Machine Learning Studio, Azure AI Foundry … AWS SageMaker, Amazon Bedrock Google Vertex AI, TensorFlow, scikit-learn, Hugging Face Data Engineering & Big Data Azure Data Factory, Azure Databricks, Apache Spark, Delta Lake AWS Glue ETL, AWS EMR Google Dataflow, Apache Beam Business Intelligence & Analytics Power BI, Amazon QuickSight, Looker Studio Embedded analytics and interactive More ❯

models using vLLM, DeepSpeed, Triton, TensorRT Multi-Agent Orchestration: Work with LangChain, AutoGen, CrewAI, DSPy and similar tools Cloud & MLOps (AWS): Deploy with SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB More ❯

models using vLLM, DeepSpeed, Triton, TensorRT Multi-Agent Orchestration: Work with LangChain, AutoGen, CrewAI, DSPy and similar tools Cloud & MLOps (AWS): Deploy with SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB More ❯

capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to More ❯