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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Amazon.com, Inc. - **Location:** Bellevue, WA, United States - **Experience:** Expert - **Salary:** $131,082.0 - $196,766.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Business Software, Databases, Continuous Integration, Information Engineering, Github, Graph Database, Python (Programming Language), Machine Learning, Role-Based Access Control, Tensorflow, Azure Machine Learning, Search Technologies, Software Construction, SQL Databases, Data Streaming, Unstructured Data, Enterprise Software Applications, Feature Engineering, Azure Data Factory, Pytorch, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Git, Microsoft Fabric, Containerization, AI Platforms, Pyspark, Information Technology, Deployment Automation, Machine Learning Operations, Artificial Intelligence Markup Language (AIML), Data Pipelines, Automation Anywhere, Software Library, Docker, Databricks, Microservices - **Published:** September 4, 2026 - **Apply:** https://www.careerjet.com/jobad/usf4bf7dd1d645d687439fc8e4812a1ca4 ## About the Role * Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence Engineering or a related field * 5 to 7 years of experience in Data Science Machine Learning AI Engineering or related disciplines * Handson experience building and deploying productiongrade AIML solutions * Strong experience with Python SQL and machine learning libraries such as Scikitlearn TensorFlow or PyTorch * Proven experience with Generative AI LLMs prompt engineering and RAG architectures * Experience with Azure AI Services Azure OpenAI Azure ML Azure AI Search Databricks or equivalent cloud AI platforms * Strong understanding of model deployment monitoring MLOps and software engineering best practices * Experience with vector databases and semantic search technologies * Familiarity with Docker Kubernetes Git and CICD pipelines * Strong analytical problemsolving and communication skills Preferred Nice to Have * Experience with Microsoft Fabric Databricks PySpark Copilot Studio or Azure AI Foundry * Experience building AI agents multiagent systems and workflow automation solutions * Knowledge of GraphRAG knowledge graphs evaluation frameworks and document intelligence solutions * Experience with realtime inference streaming data pipelines and enterprisescale AI deployments * Azure certifications such as AI Engineer Associate AI102 Azure Data Scientist Associate DP100 or Azure Fundamentals AI900 Skills Mandatory Skills : Build AI Agents using Microsoft Agent & Semantic Kernel & Langchain Framework, GenAI - LLMOps, Generative AI on Azure, MLOPS, RAGAS (Retrieval Augumented Generation Assessment) Framework Good to Have Skills : Azure Open AI Service, Responsible AI ## Description We are seeking a highly skilled AI Engineer Data Scientist with 5 to 7 years of experience in designing developing and deploying AIML solutions The ideal candidate will have strong expertise in Generative AI Large Language Models LLMs Retrieval Augmented Generation RAG Machine Learning and cloudbased AI platforms This role involves working closely with business stakeholders data engineers and application teams to develop intelligent scalable and productionready AI solutions that solve realworld business problems, AI Machine Learning Development * Design develop train and deploy machine learning and deep learning models for business use cases * Build and optimize predictive classification recommendation NLP and generative AI solutions * Perform feature engineering model selection hyperparameter tuning and model evaluation * Analyze structured and unstructured data to generate actionable insights Generative AI LLM Solutions * Develop enterprisegrade GenAI applications using Azure OpenAI OpenAI or equivalent LLM platforms * Design and implement RetrievalAugmented Generation RAG pipelines including document ingestion chunking embeddings vector search and retrieval optimization * Engineer prompts and develop agentbased workflows using frameworks such as LangChain LangGraph Semantic Kernel or AutoGen * Evaluate model performance for accuracy relevance latency safety and cost efficiency Data Engineering Solution Development * Collaborate with data engineers to build scalable data pipelines and AI workflows * Work with structured and unstructured data sources including databases APIs documents and knowledge repositories * Develop reusable AI components APIs and microservices for enterprise applications * Integrate AI solutions into business applications and enterprise platforms MLOps LLMOps Deployment * Deploy AIML solutions using Azure ML Azure AI Foundry Databricks or equivalent platforms * Implement CICD pipelines using Azure DevOps or GitHub Actions * Monitor model performance manage retraining workflows and address model drift * Utilize containerization technologies such as Docker and Kubernetes for scalable deployments * Optimize infrastructure utilization inference performance and LLM token consumption Responsible AI Security Governance * Apply Responsible AI principles including fairness transparency explainability and safety * Implement security controls RBAC data privacy measures and compliance requirements * Ensure AI applications meet enterprise governance and regulatory standards * Support monitoring auditing and operational excellence for AI solutions ## Related Videos - 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