Mogi I/O : OTT/Podcast/Short Video Apps for you
AWS Bedrock Architect – Generative AI & RAG Systems
Mogi I/O : OTT/Podcast/Short Video Apps for you, San Francisco, California, United States, 94199
AWS Bedrock Architect – Generative AI & RAG Systems
We are a leading global technology and consulting firm seeking an experienced AWS Bedrock Architect to design, implement, and scale Generative AI and Retrieval‑Augmented Generation systems using AWS Bedrock and related services. This senior‑level, highly technical role requires strong expertise in serverless architectures, agentic workflows, and AI system production.
Location:
USA – Bay Area, California Work Type:
Full‑Time (Hybrid / On‑site) Experience:
8–15 Years in Cloud Architecture and AI Systems Compensation:
$130,000 – $170,000 Annual Eligibility:
Any Visa (Excluding OPT) No‑Poach Client:
Redwood
Key Responsibilities
Architect and implement scalable Generative AI and RAG systems on AWS Bedrock.
Design and manage Bedrock Agents, action groups, knowledge bases, and orchestrate agent patterns.
Develop and optimize AWS Lambda functions (Python) for event‑driven and agentic workloads.
Design and secure API Gateway integrations for REST and WebSocket APIs.
Deploy and manage AWS Fargate for containerized and long‑running AI processes.
Automate infrastructure provisioning using AWS CDK (TypeScript or Python) and CloudFormation.
Integrate vector databases and semantic search solutions with Bedrock Knowledge Bases.
Manage RDS, Aurora, and DynamoDB for AI system data storage.
Apply advanced prompt engineering, function calling, and agent reasoning strategies.
Build and maintain CI/CD pipelines for serverless and container‑based deployments.
Collaborate with cross‑functional teams to ensure security, scalability, and cost optimization.
Present technical architectures and concepts to technical and business stakeholders.
Must‑Have Requirements
8–15 years of total IT experience with a strong focus on cloud and AI architecture.
Minimum 1 year of hands‑on experience with Generative AI and LLM‑based solutions.
Proven experience architecting and deploying serverless applications at scale on AWS.
Hands‑on experience with AWS Bedrock Agents in production environments.
Strong knowledge of RAG architectures and agentic workflow design.
Proficiency in AWS Lambda (Python) and AWS API Gateway.
Experience with AWS Fargate, CDK, and CloudFormation for multi‑service environments.
Expertise in vector databases and semantic search implementations.
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
Must currently reside in the Bay Area, CA.
Stable career history — minimum 3 years tenure with past employers.
Nice‑to‑Have Skills
Experience with AI orchestration frameworks or LLM toolchains.
Familiarity with LangChain, LlamaIndex, or similar frameworks.
Knowledge of AWS SageMaker, Step Functions, and EventBridge.
Experience deploying multi‑agent systems using Bedrock or custom orchestration layers.
Strong presentation and documentation skills for executive‑level communication.
Technical Qualifications
Deep understanding of AWS Bedrock components, Generative AI orchestration, and agent patterns.
Expertise in CI/CD pipelines, DevOps, and distributed system architecture.
Familiarity with data security and compliance within AI ecosystems.
Ability to troubleshoot complex distributed applications across AWS services.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Engineering and Information Technology
#J-18808-Ljbffr
Location:
USA – Bay Area, California Work Type:
Full‑Time (Hybrid / On‑site) Experience:
8–15 Years in Cloud Architecture and AI Systems Compensation:
$130,000 – $170,000 Annual Eligibility:
Any Visa (Excluding OPT) No‑Poach Client:
Redwood
Key Responsibilities
Architect and implement scalable Generative AI and RAG systems on AWS Bedrock.
Design and manage Bedrock Agents, action groups, knowledge bases, and orchestrate agent patterns.
Develop and optimize AWS Lambda functions (Python) for event‑driven and agentic workloads.
Design and secure API Gateway integrations for REST and WebSocket APIs.
Deploy and manage AWS Fargate for containerized and long‑running AI processes.
Automate infrastructure provisioning using AWS CDK (TypeScript or Python) and CloudFormation.
Integrate vector databases and semantic search solutions with Bedrock Knowledge Bases.
Manage RDS, Aurora, and DynamoDB for AI system data storage.
Apply advanced prompt engineering, function calling, and agent reasoning strategies.
Build and maintain CI/CD pipelines for serverless and container‑based deployments.
Collaborate with cross‑functional teams to ensure security, scalability, and cost optimization.
Present technical architectures and concepts to technical and business stakeholders.
Must‑Have Requirements
8–15 years of total IT experience with a strong focus on cloud and AI architecture.
Minimum 1 year of hands‑on experience with Generative AI and LLM‑based solutions.
Proven experience architecting and deploying serverless applications at scale on AWS.
Hands‑on experience with AWS Bedrock Agents in production environments.
Strong knowledge of RAG architectures and agentic workflow design.
Proficiency in AWS Lambda (Python) and AWS API Gateway.
Experience with AWS Fargate, CDK, and CloudFormation for multi‑service environments.
Expertise in vector databases and semantic search implementations.
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
Must currently reside in the Bay Area, CA.
Stable career history — minimum 3 years tenure with past employers.
Nice‑to‑Have Skills
Experience with AI orchestration frameworks or LLM toolchains.
Familiarity with LangChain, LlamaIndex, or similar frameworks.
Knowledge of AWS SageMaker, Step Functions, and EventBridge.
Experience deploying multi‑agent systems using Bedrock or custom orchestration layers.
Strong presentation and documentation skills for executive‑level communication.
Technical Qualifications
Deep understanding of AWS Bedrock components, Generative AI orchestration, and agent patterns.
Expertise in CI/CD pipelines, DevOps, and distributed system architecture.
Familiarity with data security and compliance within AI ecosystems.
Ability to troubleshoot complex distributed applications across AWS services.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Engineering and Information Technology
#J-18808-Ljbffr