GenAI Architect: Enterprise AI on AWS & Bedrock

Capgemini; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Capgemini is seeking a GenAI Architect in London to lead architecture and delivery of enterprise-scale AI solutions on AWS, leveraging Bedrock and RAG techniques. You will shape reusable patterns for prompt orchestration, agentic workflows, and observability while working with security, compliance and engineering teams.

The role emphasizes governance, model risk management, data privacy, and production-grade deployment in highly regulated environments.

Qualifications

• Experience designing cloud-native GenAI architectures on AWS.
• Strong governance, security, data privacy and compliance knowledge.
• Hands-on Python development for GenAI applications and APIs.
• Experience in regulated industries such as banking is highly relevant.

Responsibilities

• Lead architecture and delivery of enterprise-scale GenAI solutions on AWS.
• Define reusable architecture patterns for model customization, prompt orchestration, and retrieval pipelines.
• Design agentic AI systems with tool use, memory management, and autonomous decision flows.
• Implement observability for prompts, model responses, and agent execution workflows.
• Produce solution documentation, standards, and deployment approaches from concept to production.

Skills

GenAI architecture

Cloud-native AWS

RAG and prompt orchestration

Governance and security

Python development

Tools

Bedrock

Lambda

SageMaker

OpenSearch

ECS/EKS

API Gateway

Step Functions

S3

IAM

KMS

CloudWatch

Job description

Capgemini is seeking a GenAI Architect in London to lead architecture and delivery of enterprise-scale AI solutions on AWS, leveraging Bedrock and RAG techniques. You will shape reusable patterns for prompt orchestration, agentic workflows, and observability while working with security, compliance and engineering teams.

The role emphasizes governance, model risk management, data privacy, and production-grade deployment in highly regulated environments.