Agentic AI & Enterprise Architecture, Madrid

Agentic AI & Enterprise Architecture
Key Responsibilities

1. Agentic AI Operating Model Design
Design and implement Agentic AI-powered operating models for large-scale enterprise transformations
Architect human-AI collaboration frameworks and Digital Delivery Worker ecosystems
Create Centers of Excellence (CoE) for AI-Native delivery practices and governance
Define organizational structures, role definitions, and capability models for AI-augmented teams
Establish metrics frameworks for measuring productivity in human-AI collaborative environments

2. Enterprise Solution Architecture
Lead enterprise architecture initiatives across complex, multi-domain organizations
Design end-to-end solution architectures spanning UI, backend, data platforms, and AI services
Architect cloud-native solutions on either of AWS, Azure, and GCP with focus on scalability and resilience
Understanding of modern data architectures including data lakes, lakehouses, real-time streaming, and AI/ML pipelines
Establish architectural governance, standards, and best practices across technology stacks

3. Engineering Delivery Excellence
Design and optimize Software Development Life Cycle (SDLC) processes for AI-Native delivery
Architect CI/CD pipelines, DevSecOps practices, and automated quality gates
Lead technical due diligence and solution validation for complex transformation programs
Mentor engineering teams on modern development practices and architectural patterns
Drive adoption of platform engineering and developer experience optimization

4. Strategic Consulting Transformation
Lead C-level engagements for digital transformation and AI adoption strategies
Conduct organizational assessments and design target state operating models
Create business cases and ROI models for large-scale technology transformations
Facilitate workshops and design thinking sessions with senior stakeholders
Develop transformation roadmaps with clear milestones, dependencies, and success criteria

Required Qualifications

1. Experience Background
15+ years in enterprise architecture, solution design, and technology consulting
5+ years leading large-scale digital transformations (500+ person organizations)
3+ years hands-on experience with AI/ML platforms and Agentic AI implementations
Proven track record establishing Centers of Excellence and operating model transformations
Experience across Banking, Financial Services, or Technology sectors

2. Technical Expertise

a. Cloud Infrastructure

Expert-level proficiency in either of AWS, Azure, or GCP cloud platforms
Deep understanding of Kubernetes, Docker, microservices architecture
Experience with Infrastructure as Code (Terraform, CloudFormation, ARM templates)
Knowledge of cloud security, compliance frameworks (SOC2, PCI-DSS, GDPR)
b. Data Analytics

Expertise in modern data architecture patterns (Data Mesh, Data Fabric, Lakehouse)
Proficiency with data platforms (Snowflake, Databricks, AWS Redshift, Azure Synapse)
Experience with real-time streaming (Kafka, Kinesis, Event Hubs)
Knowledge of data governance, lineage, and quality frameworks
c. AI Machine Learning

Hands-on experience with Agentic AI platforms and multi-agent orchestration
Proficiency in LLM integration, prompt engineering, and RAG architectures
Understanding of MLOps, model lifecycle management, and AI governance
Experience with AI/ML platforms (Azure AI, AWS SageMaker, Google AI Platform)
d. Software Engineering

Proficiency in multiple programming languages (Python, Java, JavaScript, C#)
Deep understanding of API design, event-driven architecture, and integration patterns
Experience with modern frontend frameworks (React, Angular, Vue.js)
Knowledge of database technologies (SQL, NoSQL, Graph databases)
e. Leadership Consulting Skills

Executive presence with ability to influence C-level stakeholders
Proven ability to lead cross-functional teams of 20+ members
Agentic AI,AWS, Azure, GCP, Kubernetes, Docker,CI/CD, Python, Java, JavaScript, C#