1 to 25 of 77 Permanent Amazon Bedrock Jobs

integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes … sophisticated server-side and client-side features. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the … a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

contribute in this role: Architecting, building and maintaining GenAI processing pipelines/workflows in Python via technologies such as serverless functions, Airflow, MLflow, SageMaker, Bedrock, or other Working with Data and NLP Engineers and Data Scientists to automate experiments that bring ML and NLP research ideas to production Fine … with programming in Python and Jupyter notebooks Professional experience in designing, building and managing bespoke GenAI solutions in cloud environments, utilising platforms such as Amazon Bedrock Experience in building NLP solutions while consuming LLMs, either directly from third party APIs or directly from repositories such as Hugging Face … Strong, fundamental technical expertise in cloud-native technologies, such as AWS Lambda, API Gateway, SageMaker Studio, Amazon ECR, CDK, or equivalent Experience in leading/mentoring NLP/ML/GenAI engineering teams Experience in working in teams with data scientists and data engineers, for building automated pipelines for 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 ❯

prompt reasoning, and other state-of-the-art techniques to improve LLM behavior and performance. Hands-on experience using OpenAI, Azure OpenAI, Google Gemini, Amazon Bedrock, and Anthropic. Good working knowledge of these APIs as opposed to just chat-based interfaces like Claude and ChatGPT. Hands-on experience More ❯

prompt reasoning, and other state-of-the-art techniques to improve LLM behavior and performance. Hands-on experience using OpenAI, Azure OpenAI, Google Gemini, Amazon Bedrock, and Anthropic. Good working knowledge of these APIs as opposed to just chat-based interfaces like Claude and ChatGPT. Hands-on experience More ❯

orchestration platforms (e.g., Airflow). Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure, using services like AWS Bedrock, S3, SageMaker, Azure AI Search, etc. Champion ML governance by ensuring guidelines are followed, monitoring SLAs, and continuously improving the performance and reliability of 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯