1 to 25 of 38 Permanent Amazon Bedrock Jobs

Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Cloud Architect with GenAI consulting specialist? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake, Data Engineering and GenAI experience? Do you have senior stakeholder engagement experience to support pre-sales and deliver consulting engagements? Do you like to solve … Vetting Agency clearance (see ). Key job responsibilities Expertise: Collaborate with pre-sales and delivery teams to help partners and customers learn and use services such as AWS Glue, Amazon S3, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon DataZone, Amazon SageMaker, Amazon Quicksight and Amazon Bedrock. Solutions: Support pre-sales and deliver technical engagements with partners and customers. This includes participating in pre-sales visits, understanding customer requirements, creating consulting proposals and creating packaged data analytics service offerings. Delivery: Engagements include projects proving the use of AWS services to support new distributed computing solutions More ❯

Overview The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer … robust and scalable AI solutions for business problems Interact with customers directly to understand the business problem, assist in the implementation of their ML ecosystem Leverage Foundation Models on Amazon Bedrock and Amazon SageMaker to meet performance needs Analyze large historical data to automate and optimize key processes Communicate clearly with attention to detail, translating rigorous mathematical … CV, GNN, or distributed training Ability to create compelling customer proposals and present to executives; proficient English communication in technical and business settings Preferred Qualifications Experience with AWS services (Amazon SageMaker, Amazon Bedrock, EMR, S3, EC2); AWS Certification (Solutions Architect Associate, ML Engineer Associate) preferred Knowledge of AI/ML, generative AI; hands-on prompt engineering and More ❯

innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. The Role The Amazon Web Services (AWS) Senior Applied AI Architect partners with customers to design and build some of the most scalable, flexible and resilient cloud architectures and solutions. AWS Applied AI … enterprise customers through your passion for educating, training, designing and building cloud solutions. As a Senior Applied AI Architect, you will use ML and Generative AI tools, such as Amazon SageMaker, Amazon Bedrock, Amazon Q and other technologies to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. You'll help … candidates to apply. If your 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 why customers from the most More ❯

a dynamic, customer-oriented environment? As a Solutions Architect within AWS Global Sales, you will help shape and deliver strategies to build mindshare and drive adoption of AWS services (Amazon EC2, Amazon S3, Amazon DynamoDB, Amazon Bedrock) across diverse customers - from startups conceptualizing their first ideas to R&D groups within enterprise organizations. Your responsibilities … Contribute to a collaborative solutions architect team focused on continuous learning and knowledge sharing Document and share best practices within the solutions architect community About the team Diverse Experiences. Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your 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 why customers from the most successful startups to Global 500 companies More ❯

Delivery Consultant - AI/ML, Professional Services Job ID: AWS EMEA SARL (UK Branch) The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical … solutions for business problems Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs Analyze and extract relevant information from large amounts of historical data to help automate and optimize … candidates to apply. If your 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 why customers from the most More ❯

o Strong understanding of machine learning concepts, algorithms, and best practices. o Proven experience in creating, managing, and deploying ML models using core AWS services such as Amazon SageMaker (for model building, training, and deployment), EC2 (for compute instances), S3 (for data storage), and Lambda (for serverless functions). o Experience with AWS Textract for document data extraction. o … seamless data ingestion, transformation, and storage strategies within the AWS ecosystem. o Experience in optimizing AWS resource usage for cost-effectiveness and efficiency in ML operations. o Experience with Amazon Bedrock for leveraging and managing foundation models in generative AI applications. o Knowledge of database services like Amazon RDS or Amazon DynamoDB for storing metadata, features More ❯

Applied Scientist, Generative AI Innovation Center Job ID: Amazon Web Services Singapore Private Limited Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational … candidates to apply. If your 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 why customers from the most … trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/or similar tools Hands-on 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-experts Our inclusive culture empowers More ❯

Applied Scientist, Generative AI Innovation Center Job ID: Amazon Web Services Singapore Private Limited Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational … candidates to apply. If your 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 why customers from the most … trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/or similar tools Hands-on 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-experts Our inclusive culture empowers 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 ❯

and classical ML algorithms, plus deep knowledge of LLMs (prompting, fine-tuning, RAG/tool use, evaluation) Hands-on with AWS and Azure services for data/ML (e.g., Bedrock/SageMaker, Azure OpenAI/Azure ML) Strong engineering: Python, APIs, containers, Git; CI/CD (GitHub Actions/Azure DevOps), IaC (Terraform/CloudFormation) Scalable Serving Infrastructure: A 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 ❯

approaches • Experience with reinforcement learning, human feedback, and related system learning methods • Experience creating and deploying containerized AI models with Docker/Kubernetes • Working with cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) • Experience with model monitoring, A/B testing, and performance optimization • Experience with real-time inference systems and low-latency model serving • Knowledge of More ❯

approaches Experience with reinforcement learning, human feedback, and related system learning methods Experience creating and deploying containerized AI models with Docker/Kubernetes Working with cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) Experience with model monitoring, A/B testing, and performance optimization Experience with real-time inference systems and low-latency model serving Knowledge of More ❯

edge analytics capabilities. Responsibilities Design and implement data science frameworks across multi-cloud environments Develop machine learning models for data analysis and automation, including building RAG models for AWS Bedrock Automate analytic solutions and build scalable analytics capabilities Collaborate with the Mission team to gather requirements across various teams Assess and implement new technologies and tools to enhance data More ❯

proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. … with enthusiasm for MLOps tools and practices Proficiency with version control systems including Git and GitHub Other Technologies You Might Encounter Our services are deployed to AWS, typically using Bedrock, Lambda, ECS and Kubernetes with CloudFormation and CDK for infrastructure configuration Our web products are developed using TypeScript, React, and Redux We implement GraphQL and RESTful APIs using NodeJS More ❯

2.x, tiny-SD) Frameworks: Python (scikit-learn, pandas, NumPy), Keras, TensorFlow, Pyspark, Streamlit Data Visualization Tools: Matplotlib, Seaborn, Advanced Excel Cloud: S3, Lambda, API Gateway, EC2, Athena, Glue, OpenSearch, Bedrock, SageMaker, Azure Functions, Azure SQL, Azure ML Studio, GCP Vertex AI, GitHub Database: MySQL, Postgres, BigQuery Location: Preferred Sunnyvale/Bay Area; PST time zone coverage required. More ❯

and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate large language models (OpenAI, Bedrock, etc.), manage prompts, tools, safeguards, and evaluation. Data pipelines: Ingest, clean, and transform structured and unstructured data; design efficient schemas (Postgres/NoSQL) for search and analytics. Frontend (React More ❯

Plan Free breakfast and beverages Requirements Proven experience in .NET Core/C# and modern web frameworks like Angular/TypeScript Hands-on experience with LLM APIs (OpenAI, Claude, Bedrock), LangChain, or RAG-based architectures Deep familiarity with API design, microservices, and cloud-first development (AWS, Azure, or GCP) Experience building systems with MongoDB, SQL, or vector databases like More ❯

Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration: Integrate OpenAI/Bedrock models, prompt/response orchestration, tool use, guardrails, and evaluation. Data pipelines: Ingest and transform structured/unstructured data; design efficient schemas (Postgres/NoSQL) to support retrieval and More ❯

Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration: Integrate OpenAI/Bedrock models, prompt/response orchestration, tool use, guardrails, and evaluation. Data pipelines: Ingest and transform structured/unstructured data; design efficient schemas (Postgres/NoSQL) to support retrieval and More ❯

with AI models and data platforms. Frontend Development: Develop responsive, high-performance user interfaces with React/Next.js. AI Integration: Connect to LLMs and ML services (e.g., OpenAI, AWS Bedrock), supporting prompt engineering, embeddings, and vector databases. Data Engineering: Handle structured and unstructured data, build ingestion pipelines, and design efficient schemas (Postgres/NoSQL). Architecture & Design: Influence technical More ❯

e.g., chatbots, summarization tools, recommendation engines). • Knowledge of application compatibility, security, and performance optimization. • Familiarity with AWS services related to frontend deployment and GenAI model hosting (e.g., SageMaker, Bedrock). Preferred Skills: • Experience with Angular and hybrid frontend architectures. • Exposure to CI/CD pipelines and cloud-native development practices. • Familiarity with GenAI frameworks and libraries (e.g., LangChain More ❯