1 to 25 of 63 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 ❯

Data Scientists to containerize and productionize models and algorithms, including those involving RAG and Graph RAG approaches. Manage and optimize our cloud infrastructure for ML workloads on platforms like Amazon Bedrock or similar, focusing on performance, cost-effectiveness, and scalability. Automate the provisioning of ML infrastructure using Infrastructure as Code (IaC) principles and tools. Work closely with product … Java or TypeScript environments is beneficial. Deep experience with at least one major cloud provider (AWS, GCP, Azure) and their ML services (e.g., SageMaker, Vertex AI). Experience with Amazon Bedrock is a significant plus. Strong familiarity with containerization (Docker) and orchestration (Kubernetes). Experience with Infrastructure as Code (e.g., Terraform, CloudFormation). Experience in deploying and managing More ❯

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 … and orchestration approaches Hands-on 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 your passion to discover, invent, simplify and build. Protecting your privacy and the security of More ❯

you will be responsible for driving strategy, top line revenue growth and overall end customer adoption of our comprehensive GenAI/ML solutions. AI/ML services such as Amazon Nova, Amazon SageMaker, Amazon Bedrock, and our generative AI offerings. You will lead a senior go-to-market team across 100+ countries in EMEA, leveraging sales … on thinking big, delivering exceptional results for our customers, and working across AWS as to build the future of AI and cloud computing. This position is part of the Amazon Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains, providing the business and technical expertise to 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 ❯

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 … business problems 2. Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem 3. Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs 4. Analyze and extract relevant information from large amounts of historical data to help automate and … 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 ❯

strategy, consulting, or software development Prior consulting experience essential Strong technical knowledge of GenAI and ML, including LLMs, RAG, MLOps, and prompt engineering Familiarity with platforms such as AWS Bedrock, Google Vertex, LangChain, or LlamaIndex Experience with both legacy systems and modern tech stacks Proven track record in agile delivery and digital transformation Excellent communication, analytical, and stakeholder management 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 ❯

service industry including: Retrieval-Augmented Generation (RAG), GraphRAG, query expansion, map reduce, maximum marginal relevance retrieval and other GenAI techniques. Familiarity with cloud platform providers (minimum of 1): AWS: Amazon SageMaker, Bedrock (Titan, Claude, etc.), CodeWhisperer, Amazon Transcribe, Amazon Comprehend, etc. Azure: Azure OpenAI Service (Gemini, GPT, DALL-E, Codex), Azure Machine Learning, Cognitive Services (Speech More ❯

embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB) databases Strong More ❯

the right fit for Deloitte landscape and uses cases. 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 ❯

the right fit for Deloitte landscape and uses cases. 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 ❯

the right fit for Deloitte landscape and uses cases. 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 ❯

the right fit for Deloitte landscape and uses cases. 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 ❯

the right fit for Deloitte landscape and uses cases. 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 ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps 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 ❯

and libraries. Hands-on experience with cloud technologies and services (e.g., AWS, Azure, Google Cloud) Experience with SQL and/or Snowflake. Some experience with Generative AI technologies (e.g. Bedrock, Langchain, LangGraph). Terms like RAG and Graphs are nothing new for you. Proficiency in data preprocessing and feature and/or prompt engineering. Customer-focused engineer with a More ❯

and libraries. Hands-on experience with cloud technologies and services (e.g., AWS, Azure, Google Cloud) Experience with SQL and/or Snowflake. Some experience with Generative AI technologies (e.g. Bedrock, Langchain, LangGraph). Terms like RAG and Graphs are nothing new for you. Proficiency in data preprocessing and feature and/or prompt engineering. Customer-focused engineer with a More ❯

as multi-class classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services , AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelors degree (masters or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related technical field 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 ❯

leadership An understanding of AI, and AI ethics An understanding of data safety in use of Large Language Models Knowledge and experience of either AWS or Azure: AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2) Azure (azure Open AI service, Cosmos DB) Python Langgraph Neo4j/cypher Other coding languages/frameworks e.g. Java/.Net AI RAG (retrieval augmented More ❯

OpenAI-based solutions and Microsoft Copilot, with a strong emphasis onsecurity, compliance, and responsible AI use. The ideal candidate will have hands-on experience with OpenAI APIs, Microsoft Copilot Amazon Bedrock, and will serve as a bridge between engineering, information security, and business stakeholders-especially within the investor community. RESPONSIBILITIES AI Tool Strategy & Governance Define and maintain standards … drift. Work closely with InfoSec and Legal to ensure all AI deployments meet compliance standards Innovation & Thought Leadership Monitor and evaluateemerging AI capabilitiesand product enhancements from Microsoft, OpenAI, and Amazon Bedrock. Contribute to internal knowledge sharing and represent the team in AI working groups and forums. QUALIFICATIONS Strong understanding ofinformation security principlesandAI governance. Excellent communication and stakeholder management skills. …/ML or NLP. Proficiency withOpenAI APIs,Azure OpenAI, andCopilot Studio. Azure and SSO Administration experience is a nice to have. Familiarity withAWS AI/ML services(e.g., SageMaker, Bedrock, Comprehend). Experience with Harmonic AI or Prompt AI would be a nice to have. Must be able to work in Boston or Needham - 4 days a week onsite. More ❯

big data technologies and cloud-based technologies AWS Services, State Machines, CDK, Glue, TypeScript, CloudWatch, Lambda, CloudFormation, S3, Glacier Archival Storage, DataSync, Lake Formation, AppFlow, RDS PostgreSQL, Aurora, Athena, Amazon MSK, Apache Iceberg, Spark, Python ONSITE: Partially onsite 3 days per week (Tue, Wed, Thurs) and as needed. Standard work hours: 8:30 AM - 5:00 PM Required Qualifications … related degree 6 years-of application development, systems testing Nice to have: AWS Redshift, Databricks- delta Lake, Unity catalog, Data Engineering and processing using Databricks, AI and Machine Learning Amazon Bedrock, AWS Sagemaker, Unified Studio, R Studio/Posit Workbench, R Shiny/Posit Connect, Posit Package Manager, AWS Data Firehose, Kafka, Hive, Hue, Oozie, Sqoop, Git/ More ❯

management and organizational skills Preferred Qualifications: Generating Echo handlers and models from OAS using oapi-codegen Launch Darkly Feature Flagging Docker AWS Cloud Services including EKS and RDS AWS Bedrock Knowledgebases and Agents AWS Sagemaker Generative AI Prompt Engineering Additional Information About QAD: QAD Inc. is a leading provider of adaptive, cloud-based enterprise software and services for global More ❯