Generative AI Platform Architect – AWS Bedrock & Cloud Automation

Mogi I/O : OTT/Podcast/Short Video Apps for you; San Francisco (CA); Hybrid; USD 130,000 - 170,000; Full time

Job summary

A leading global technology and consulting firm is seeking an AWS Bedrock Architect to design, implement, and scale Generative AI systems using AWS. The ideal candidate should have extensive experience in cloud architecture and hands-on expertise with AWS Bedrock. This role supports hybrid work options and requires residence in the Bay Area, California. Compensation is between $130,000 and $170,000 annually.

Qualifications

• 8–15 years of total IT experience focused on cloud and AI architecture.
• 1 year of hands-on experience with Generative AI and LLM-based solutions.
• Proven experience architecting and deploying serverless applications on AWS.

Responsibilities

• Architect and implement scalable Generative AI and RAG systems on AWS Bedrock.
• Design and manage Bedrock Agents including action groups.
• Develop and optimize AWS Lambda functions for event-driven workloads.

Skills

AWS Bedrock

Generative AI

RAG architectures

AWS Lambda (Python)

AWS Fargate

CloudFormation

Vector databases

Semantic search

CI/CD pipelines

DevOps

Education

Bachelor’s or Master’s degree in Computer Science or IT

Tools

AWS Bedrock Agents

AWS API Gateway

AWS CDK

Job description

Location: USA – Bay Area, California

Work Type: Full-Time (Hybrid / On-site)

Experience Required: 8–15 Years in Cloud Architecture and AI Systems

Compensation: USD 130,000 – 170,000 Annual

Eligibility: Any Visa (Excluding OPT)

Job Overview

A leading global technology and consulting firm is seeking an AWS Bedrock Architect to design, implement, and scale Generative AI and RAG-based architectures leveraging AWS Bedrock. The ideal candidate will have hands‑on expertise in building agentic workflows, knowledge bases, and serverless applications, and will be responsible for developing high‑performance, production‑grade Generative AI systems using AWS native services.

Key Responsibilities

• Architect and implement scalable Generative AI and RAG (Retrieval‑Augmented Generation) systems on AWS Bedrock.
• Design and manage Bedrock Agents including action groups, knowledge bases, and agent orchestration patterns.
• Develop and optimize AWS Lambda functions (Python) for event‑driven and agentic workloads.
• Design and secure AWS 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 of AI workloads.
• Present technical architectures and concepts to both technical and business stakeholders.

Must-Have Requirements

• 8–15 years of total IT experience with 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 on AWS at scale.
• 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.