AI Foundations Architect

Keyrus

. Design the architecture of intelligence systems, including data flows, model integration, and the technical orchestration of agents .

Posted 10/13/2026full-timeBordeaux • FranceSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing complex technical architectures, including data platforms and AI systems, while ensuring scalability, security, and governance. Proficient in collaborating with cross-functional teams to document and communicate architectural decisions effectively.

Highest-signal resume keywords

Complex Technical Architecture DesignData Platform ImplementationSystem Security and Access GovernanceMLOps PracticesCloud Deployment (Azure, GCP, AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureModel IntegrationTechnical OrchestrationEvent-Driven ArchitectureStreaming Systems (Kafka)Feature Store DesignObservability and MonitoringInfrastructure as Code (Terraform)AI FinOps ManagementIntegration of LLMs and Vector Databases

Soft Skills

Strong RigorHigh Technical StandardsClient EngagementDocumentation and Communication

Tools & Technologies

Palantir FoundryAIPAnthropic ModelsOpenAI ModelsMistral ModelsGoogle Gemini Models

Industry Keywords

Data MeshData FabricDistributed SystemsScalabilityResilience

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformKafkaTerraformTypeScript

About the role

Key responsibilities & impact

Design the architecture of intelligence systems, including data flows, model integration, and the technical orchestration of agents
Define the constraints and possibilities for the Forward Deployed Engineer, both ahead of and in support of missions
Ensure the scalability, resilience, and security of deployed systems
Collaborate with the AI Engineer on architecture implementation and with the Software Engineer on application integration
Make decisions regarding routing/cascading, tiering, and inference costs across models as part of AI FinOps
Define standards and produce technical documentation to support the handover and evolution of systems
Work with the Data Engineer, Data Trust & AI Governance Manager, Service Delivery Manager, and Business Value Advisor to ensure technical consistency, governance, operations, and business alignment

Requirements

What you’ll need

More than 8 years of experience designing and implementing complex technical architectures (data, cloud, and distributed systems)
Proven experience bringing systems into production at scale
Experience addressing security and access governance requirements in production environments
Ability to think in terms of systems before focusing on technology
Strong rigor and high technical standards
Ability to support the Forward Deployed Engineer and AI Engineer, and to engage directly with clients when necessary
Ability to develop, document, and communicate architectural decisions
Design of intelligence system architectures, model integration, and technical orchestration of agents
Design of modern data platforms (lakehouse, data mesh, data fabric) and enterprise AI platforms (Palantir Foundry / AIP or equivalent)
Implementation of data infrastructure and MLOps practices
Design of event-driven architectures and streaming systems at scale (Kafka)
Design of feature stores and model-serving infrastructure
System security and access governance
Integration of LLMs and vector databases
Implementation of observability and monitoring for distributed systems
Deployment on Azure, GCP, or AWS, and infrastructure-as-code management with Terraform
Comparative expertise in Anthropic, OpenAI, Mistral, and Google Gemini models and providers
Management of inference costs, routing/cascading, and tiering as part of AI FinOps
Preparation of technical architecture documents and documentation
Professional fluency in written and spoken English is essential

Benefits

Comp & perks

A multicultural, enriching environment that encourages international mobility
Initiative and teamwork are valued
Collaboration with diverse areas of expertise, business functions, and geographies