Generative AI Architect

Overview

Hybrid
Depends on Experience
Full Time

Skills

Bedrock
RAG
Gen AI

Job Details

Job Description

We are seeking an experienced technologist to architect and implement enterprise-grade Agentic AI solutions on AWS Bedrock platform. You will extend solutions involving RAG architecture and Bedrock Agents, designing scalable serverless systems using AWS native services. This role demands deep expertise in Generative AI technologies and hands-on experience building production-grade AI systems on AWS.

Roles & Responsibilities

Key Responsibilities

- Architect and implement the evolution from RAG-based systems to Agentic AI solutions using AWS Bedrock Agents
- Design and build serverless architectures leveraging Lambda, API Gateway, and Fargate for scalable AI workloads
- Lead architecture design sessions to define technical standards, patterns, and implementation guidelines for agent-based systems
- Develop Infrastructure as Code using AWS CDK and CloudFormation for repeatable, maintainable deployments
- Collaborate with stakeholders to translate business requirements into scalable technical solutions
- Provide technical mentorship to engineering teams on Bedrock Agents, serverless patterns, and best practices
- Ensure compliance with security regulations, implementing guardrails and governance for AI systems
- Evaluate and prototype emerging capabilities in the Bedrock ecosystem to enhance existing architectures

Required Skills and Technologies

- Extensive hands-on experience with AWS Bedrock Agents including action groups, knowledge bases, and orchestration patterns
- Strong expertise in RAG architectures with proven experience extending to agentic workflows
- Proficiency in AWS Lambda development with Python, including complex event-driven architectures
- Deep knowledge of AWS API Gateway for REST and WebSocket APIs, including custom authorizers and integration patterns
- Experience with AWS Fargate for containerized workloads and long-running agent processes
- Strong expertise in AWS CDK (TypeScript or Python) and CloudFormation for infrastructure automation
- Deep Knowledge and experience of vector databases and semantic search integration with Bedrock knowledge bases
- Experience with both SQL databases (RDS, Aurora) and NoSQL solutions (DynamoDB)
- Understanding of prompt engineering, function calling, and agent reasoning patterns
- Proficiency in CI/CD pipelines for serverless applications and container deployments
- Strong problem-solving abilities with systematic approaches to distributed system challenges
- Excellent communication skills to explain complex AI architectures to diverse audiences

Technical Qualifications

- Bachelor's or Master's degree in Computer Science, Information Technology, or related technical field
- Minimum 1 years of hands-on experience with Generative AI and LLM-based solutions
- Proven experience architecting and deploying serverless applications on AWS at scale
- Demonstrated expertise building RAG systems and extending them to agent-based architectures
- Strong track record with AWS CDK/CloudFormation for complex multi-service deployments
- Experience with Bedrock Agents in production environments

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.