17 of 17 Remote Amazon Bedrock Jobs

Experience with ML lifecycle management tools like AWS SageMaker, MLflow, or Databricks. Working knowledge of CUDA, Nvidia GPUs, and distributed training. Experience with AWS services (S3, Lambda, EC2, SageMaker, Bedrock, etc.). Desired: Experience deploying models as APIs/microservices in cloud-native environments. Familiarity with prompt tuning, embedding generation, vector search, and knowledge retrieval frameworks. Understanding of MLOps 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 ❯

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 ❯

e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Cloud platform experience, especially from an ML standpoint (AWS preferred) Statistical testing experience Experience with AWS Bedrock Experience with C# Containerization via Docker. Awareness of basic data science and generative AI methods. Exposure to generative AI application frameworks like LangChain, LlamaIndex, SmolAgents and griptape. What's 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 ❯

across multiple teams. • Extensive experience in large scale machine learning, including building, deploying, scaling and securing ML infrastructure in cloud-native environments. • Strong experience with AWS services including SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, DynamoDB, Kafka, CloudFormation and associated technologies such as Python • Proven ability to drive cross functional technical initiatives and deliver results through 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 ❯

performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. Integrate semantic search strategies and embeddings to improve LLM relevance and contextual understanding. Build demo-ready user interfaces with tools like Streamlit More ❯

performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. Integrate semantic search strategies and embeddings to improve LLM relevance and contextual understanding. Build demo-ready user interfaces with tools like Streamlit 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 ❯

complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React; familiarity with microservices More ❯

need 4+ years of backend engineering experience Strong experience with Python, Java or Kotlin in production environments Experience designing and maintaining scalable services Familiarity with modern AI providers (AWS Bedrock, Open AI, Anthropic, etc) Proficiency in modern development practices (CI/CD, observability, test automation) A passion for building tooling that accelerates innovation Strong ownership mindset and collaborative approach More ❯

a practical, down-to-earth approach. Nice to have Experience testing AI/LLM-based solutions, including model accuracy, correctness, and performance validation. Familiarity with Azure OpenAI Service, AWS Bedrock, or similar AI platforms. Experience testing OfficeJS applications or add-ins. Background in the LegalTech domain or other highly regulated industries. QA certifications (e.g., ISTQB) or other relevant software More ❯

client workstreams and in the technology department as a whole. Technical skills and knowledge: Cloud hosting providers such as AWS, Azure, GCP, Vercel & Netlify AI platforms such as AWS Bedrock, Microsoft Azure AI, Google Vertex AI AI frameworks such as AutoGen, Langflow Fine-tuned and train AI models Knowledge of Infrastructure as Code, CI/CD Use of Middleware More ❯

AI agents Design and develop RAG (Retrieval-Augmented Generation) operations to enhance AI model performance Create and maintain prompt workflows for various AI tasks Integrate and work with AWS Bedrock and Bedrock knowledgebases Utilize Anthropic Claude Sonnet for advanced language processing tasks Works closely with business analysts, UI/UX developers, and subject matter experts to understand functional … web application development using .NET and C# Strong proficiency in front-end technologies (HTML5, CSS, JavaScript) Experience with MySQL database design and management Familiarity with AWS services, particularly AWS Bedrock Knowledge of Generative AI concepts and technologies Experience with implementing chatbots or conversational AI systems Understanding of RAG operations and prompt engineering Familiarity with large language models like Anthropic More ❯

support and development to succeed. A progressive organisation where you can really make a difference. We a great opportunity for a Data Scientist. You will have solid experience of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas … Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration in AWS. OCR Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging … actionable insights. Stakeholder Collaboration: Effective communication with technical and non-technical stakeholders. Experience in cross-functional team. Data Engineering Basics: Familiarity with SQL and big data processing tools (e.g., Amazon Athena). Model Evaluation & Experimentation: A/B testing, statistical analysis, and performance metrics. Security & Compliance Awareness: Understanding of data privacy, PII handling, and compliance standards (e.g., GDPR). More ❯

role is for you. Important: Only candidates with active SC clearance can be considered. What You'll Do: Design and build robust backend services using Next.js, Node.js, and AWS Bedrock Architect and implement MCP servers to support dynamic agent creation and deployment Develop scalable, secure RESTful APIs and GraphQL endpoints Integrate AWS foundation models and optimise their performance across … CD pipelines using GitLab Contribute to containerisationand deployments on OpenShift What You'll Bring: 3+ years backend development experience with Node.js/Next.js Proven experience with AWS services (particularly Bedrock & AI/ML integrations) Strong understanding of REST APIs, microservices, and secure coding Experience with CI/CD pipelines (GitLab preferred) Solid background in SQL and NoSQL databases Ability More ❯