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Artefact

Data and AI-driven business transformation consulting

Manager AI Architect

Technology & Systems ConsultingUpdated on Nov 14
Full-timeParis, FranceIn-person

About the Job

Requirements

  • You have designed a data or AI architecture that went into production, and you can explain why you rejected other technical or nontechnical options.
  • You have recommended a technically less attractive option because it better matched a client's budget, skills, governance, or regulatory requirements.
  • You are proficient with at least one major cloud platform: Google Cloud, Azure, or AWS, and understand security and networking fundamentals, including IAM, secrets management, and network architecture.
  • You have written high-level and low-level architecture documents that served as a basis for a delivery team.
  • You have coded for a significant part of your career and can now read code, challenge a design, and identify what a production system requires, including CI/CD, monitoring, and incident management.
  • You have scoped and priced a solution, for example for a commercial proposal or project plan.
  • You have defended an architecture to both business leadership or an executive committee and security and operations teams, connecting business value, technical choices, and the delivery plan.

Responsibilities

  • Translate client objectives, constraints, and timelines into an architecture understood by both business and IT stakeholders, and defend the design choices.
  • Design data and agentic platforms on premise, in the cloud, or in hybrid environments.
  • Divide technical scopes according to how the client's teams are organized.
  • Evaluate options by weighing business value, total cost, compliance, vendor dependence, and the client's ability to operate the solution.
  • Help clients evaluate and competitively assess vendors impartially.
  • Prepare commercial proposals by scoping and pricing the solution and building the delivery roadmap.
  • Guide the architecture through delivery by reviewing designs, resolving trade-offs, and adjusting the target architecture as the client's context changes.
  • Maintain the chapter's reference patterns and best practices, and track developments in AI, cloud, and data.
  • Work closely with AI Applied Engineers who build and operate the designed systems and AI Product Managers who own the product with the client.
  • Align client business leadership and IT, security, network, and operations teams on the architecture, and engage procurement, compliance, and vendors.
  • Review peers' designs, help develop architects and engineering colleagues, share effective practices, and work with technology partners and other Artefact teams.

Desired Qualifications

  • Experience with agentic platform architecture, including retrieval-augmented generation, multi-agent orchestration, and selecting technologies layer by layer.
  • Enterprise-scale data governance experience, including data mesh and access management.
  • Experience with on-premise, hybrid, or sovereign platforms based on open-source technologies or Kubernetes.
  • Familiarity with operational standards such as service-level agreements, disaster recovery plans, and business continuity plans.
  • Experience as a chief technology officer or technical lead, or in a client-facing role.
  • A cloud architecture certification.
  • Regular use of coding agents.

About the Company

Artefact

Data and AI-driven business transformation consulting

Artefact helps organizations use data and AI to transform their operations and decision-making. It provides end-to-end services across the data value chain, from strategy and data platform implementation to governance, advanced analytics, and sector-specific AI tools, delivered through consulting and project execution. The company works with industries like FMCG, retail, and luxury goods to optimize marketing performance, customer engagement, and ROI. Artefact differentiates itself by combining consulting expertise with data science and AI capabilities across multiple regions, offering integrated, sector-focused solutions rather than just advisory services. The main goal is to help clients adopt data-driven approaches to improve efficiency, decision quality, and marketing results at scale.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Paris, France
Founded
1998

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