151 to 175 of 297 Permanent Amazon Bedrock Jobs

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Salesforce, Snowflake, and UiPath Strong expertise in Data Engineering, Machine Learning, Generative AI, RAG, and Agent AI Proficiency with modern AI tools and frameworks: Amazon Bedrock, Hugging Face, Claude, LLaMA, OpenAI, Grok Hands-on experience with code-gen tools like Cursor, Replit, and working on: Software code/ 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 ❯

Design, develop, and deploy AI systems that can run efficiently in on-premise environments with local models, without depending on 3rd parties like OpenAI, Amazon Bedrock, etc. Optimize Small Language Models (SLMs) for private deployments with attention to performance and resource constraints. Contribute to the architecture of our More ❯

been tried before. Challenge conventional wisdom about what's possible with current AI technologies. Required Skills & Experience: Experience with AWS AI services (e.g., AWS Bedrock, SageMaker Studio, Lambda, EKS ) and/or Azure AI services (e.g., Azure OpenAI, Azure Cognitive Service, Azure ML). Experience with designing, building and More ❯

been tried before. Challenge conventional wisdom about what's possible with current AI technologies. Required Skills & Experience: Experience with AWS AI services (e.g., AWS Bedrock, SageMaker Studio, Lambda, EKS ) and/or Azure AI services (e.g., Azure OpenAI, Azure Cognitive Service, Azure ML). Experience with designing, building and More ❯

been tried before. Challenge conventional wisdom about what's possible with current AI technologies. Required Skills & Experience: Experience with AWS AI services (e.g., AWS Bedrock, SageMaker Studio, Lambda, EKS ) and/or Azure AI services (e.g., Azure OpenAI, Azure Cognitive Service, Azure ML). Experience with designing, building and More ❯

been tried before. Challenge conventional wisdom about what's possible with current AI technologies. Required Skills & Experience: Experience with AWS AI services (e.g., AWS Bedrock, SageMaker Studio, Lambda, EKS ) and/or Azure AI services (e.g., Azure OpenAI, Azure Cognitive Service, Azure ML). Experience with designing, building and 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 More ❯

as getting your fingers on key boards to build them. Strong experience with AWS data services with exposure to AI systems (e.g., AWS DataZone, Bedrock, Redshift, Glue ) and/or Azure data services (e.g., Azure OpenSearch, Azure OpenAI, Fabric, Purview, Data Factory, Synapse ) Proficiency with Python for data processing More ❯