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# Principal Data Architect

- **Company:** Capgemini
- **Location:** London, UK (Remote available)
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Audit Trail, Data Architecture, Dataspaces, Distributed Systems, Memory Management, Identity and Access Management, Python (Programming Language), Performance Tuning, Software Deployment, Workflow Management Systems, Enterprise Software Applications, State Machines, Model Validation, Generative AI, Machine Learning Operations, Cloudwatch, Api Gateway
- **Published:** June 12, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=2ba574b434c9346d

## About the Role

Do you have experience in Software deployment?, * Experience designing cloud-native GenAI architectures using AWS services such as Bedrock, Lambda, SageMaker, OpenSearch, ECS/EKS, API Gateway, Step Functions, S3, IAM, KMS, and CloudWatch

 * Knowledge of scalable, secure, event-driven, and distributed system architectures
 * Experience integrating structured and unstructured enterprise data sources
 * Experience with RAG, fine-tuning, model evaluation, data privacy, ethical AI, and cross-functional stakeholder management is expected
 * Strong understanding of enterprise security architecture, IAM, encryption, and secure AI deployment practices
 * Experience implementing AI governance, auditability, data privacy, and compliance controls
 * Banking or regulated-industry experience is highly relevant
 * Hands-on Python development experience for building GenAI applications, APIs, orchestration pipelines, and automation workflows is preferred

## Description

* Lead architecture and implementation of GenAI applications using AWS services, especially large language model capabilities such as Amazon Bedrock
 * Define reusable architecture patterns for model customization, prompt orchestration, retrieval pipelines, and agentic workflows
 * Design agentic AI systems incorporating tool use, workflow orchestration, memory management, and autonomous decision flows
 * Implement observability for prompts, model responses, vector retrieval quality, and agent execution workflows
 * Integrate GenAI capabilities into enterprise applications, APIs, workflow platforms, and data ecosystems
 * Work with security, risk, compliance, engineering, and business teams to enable LLMOps and AgenticOps capabilities - prompt lifecycle management, model observability, caching, evaluation and governance.
 * Ensure compliance with enterprise governance, model risk, auditability, data privacy, and regulatory requirements in highly regulated environments
 * Produce solution documentation, technical standards, and deployment approaches, and support delivery from concept through production.


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