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Accenture

Advises businesses and runs their technology

AI Architecture Director - Generative AI & AI Transformation

Technology & Systems ConsultingConfirmed live in the last 24 hours
Full-timeMadrid, SpainNo salary listedIn-person

About the Job

Requirements

  • A minimum of 10 years of professional experience in technology consulting, digital transformation, or enterprise architecture is required.
  • A minimum of 2 years of professional experience participating in artificial intelligence projects is required.
  • A minimum of 5 years of professional experience leading technology or transformation programs for large organizations is required.
  • Professional experience with artificial intelligence architecture initiatives, Generative AI, or artificial intelligence platforms in enterprise environments is required.
  • Professional experience defining enterprise cloud architectures on Microsoft Azure, Amazon Web Services, or Google Cloud Platform is required.
  • Professional experience designing solutions based on Large Language Models, Generative AI, and AI agents is required.
  • Professional experience in strategic or technology consulting is required.
  • Professional experience building technology business cases and analyzing costs, benefits, and investment is required.
  • Professional experience in at least one of these sectors is required: Consumer, Retail, Travel, Industrial, Construction, or Life Sciences.
  • C1-level English is required.
  • Experience with enterprise data platforms such as Databricks, Microsoft Fabric, or Snowflake is required for the role's duties.
  • Knowledge and experience using generative artificial intelligence and workplace AI tools is required, in accordance with the employer's responsible and effective AI use approach.

Responsibilities

  • Lead artificial intelligence, Generative AI, and Agentic AI transformation programs for large clients, identifying use cases, defining target architectures and operating models, and taking initiatives from strategy through implementation and scaling.
  • Design enterprise artificial intelligence architectures integrating cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform; Large Language Models; AI agents; enterprise systems; data platforms; and integration, governance, and security mechanisms.
  • Design and build AI context architectures and databases that enable Large Language Models and agents to access, retrieve, and use enterprise information in a structured way, including contextualization and information-retrieval patterns for solutions based on models such as GPT and Claude.
  • Define architectures and methodologies for applying Agentic AI in technology functions, including the Technology Development Life Cycle, demand management, and functional analysis, establishing differentiated patterns and capabilities at corporate, departmental, and project levels.
  • Define enterprise Agentic AI and Generative AI architectures aligned with business objectives, technology architecture, and governance requirements of large organizations.
  • Design the architecture needed to deploy Agentic AI capabilities, including Large Language Models, agents, orchestration, context layers, information-retrieval systems, enterprise-system integrations, data platforms, and cloud services.
  • Define the architectural model for an agentic Technology Development Life Cycle, determining which components, services, and capabilities should be reusable corporate platforms, which belong at departmental level, and which should be designed for individual projects.
  • Design context architectures that enable AI agents and models to use enterprise knowledge and data from multiple sources, considering Retrieval-Augmented Generation, semantic search, vectorization, and context management patterns.
  • Apply Agentic AI to technology-function processes beyond software development, including demand management, functional analysis, architecture, engineering, testing, operations, and maintenance.
  • Apply process-reinvention methodologies to identify activities that can be transformed using AI agents, redesign workflows, and define new interaction models between people, agents, and enterprise systems.
  • Evaluate and select AI platforms, Large Language Models, cloud services, data platforms, and technology ecosystems suitable for complex enterprise environments.
  • Define AI operating models, adoption strategies, and governance, security, Responsible AI, and scalability mechanisms.
  • Build AI business cases quantifying costs, benefits, operational efficiency, return on investment, and initiative prioritization.
  • Lead multidisciplinary teams of architects, consultants, data specialists, and AI engineers.
  • Present architectures, roadmaps, transformation proposals, and business cases to CIOs, CTOs, CDOs, and other executive stakeholders.
  • Contribute to commercial growth by identifying opportunities and developing value propositions for AI Transformation, Generative AI, and Agentic AI.

Desired Qualifications

  • Experience designing context architectures for Large Language Model and AI-agent solutions, including Retrieval-Augmented Generation, semantic search, vectorization, enterprise knowledge retrieval, and context management.
  • Experience defining architectures for Agentic AI and agent models integrated with enterprise processes and systems.
  • Experience applying Agentic AI to the Technology Development Life Cycle and technology processes such as demand management, functional analysis, architecture, engineering, testing, or operations.
  • Experience defining differentiated AI architectures and capabilities at corporate, departmental, and project levels.
  • Experience with process-reinvention or redesign methodologies using Generative AI and Agentic AI.
  • Microsoft Azure AI Engineer Associate, Azure Solutions Architect Expert, or equivalent certification.
  • AWS Certified Machine Learning, AWS Certified Solutions Architect – Professional, or equivalent certification.
  • Experience with enterprise adoption of Generative AI and Agentic AI at scale.
  • Experience with AI governance, Responsible AI, or AI Risk Management strategies.
  • Experience participating in AI transformation programs for IBEX 35 companies or large multinational corporations.
  • Experience leading distributed international teams.

About the Company

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Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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