AI Workflow Architect

CRAFT; Madrid; Presencial; EUR 70.000 - 90.000; Jornada completa

Descripción de la vacante

A technology firm in Madrid seeks an experienced AI Workflow Architect to design and implement scalable AI workflows. Responsibilities include architecting end-to-end workflows and collaborating with cross-functional teams to embed AI systems. The ideal candidate has 5+ years in AI engineering and is proficient in Python and cloud infrastructures. This role offers a competitive salary and focuses on innovative automation strategies.

Formación

• 5+ years of experience in software architecture, AI engineering, or automation design.
• Hands-on experience with AI / ML lifecycle tools.
• Strong understanding of workflow orchestration systems.

Responsabilidades

• Architect end-to-end AI workflows from data ingestion to deployment.
• Design orchestration strategies using tools like Airflow or Prefect.
• Establish monitoring and auditing mechanisms to ensure reliability.

Conocimientos

AI / ML lifecycle tools

Workflow orchestration systems

Python

APIs (REST / GraphQL)

Cloud infrastructure (AWS, GCP, Azure)

Educación

Bachelor’s or Master’s degree in Computer Science, AI, Data Engineering

Herramientas

Apache Airflow

MLflow

LangChain

Hugging Face

Descripción del empleo

We are seeking a forward-thinking AI Workflow Architect to design and implement scalable AI-powered workflows across business units. This role combines deep technical knowledge of AI / ML technologies with a strong understanding of business processes to architect intelligent systems that improve efficiency, reduce operational friction, and unlock new capabilities across the enterprise. You will serve as a key link between technical engineering teams, data scientists, and business stakeholders to build AI-driven automation pipelines, orchestration layers, and decision systems. You’ll also be responsible for ensuring governance, scalability, and sustainability of these workflows. Key Responsibilities

• Workflow Design & Architecture
• Architect end-to-end AI workflows from data ingestion to model deployment and decision-making.
• Design orchestration strategies using tools like Airflow, Prefect, or custom solutions.
• Define interfaces between AI models, APIs, business logic, and human-in-the-loop components.
• Integration & Automation
• Integrate AI systems into business operations using APIs, RPA tools, and platform-specific SDKs (e.g., OpenAI, Google Vertex, Azure AI).
• Collaborate with IT and DevOps teams to embed workflows within enterprise software ecosystems (CRM, CMS, DAM, ERP).
• Cross-functional Collaboration
• Partner with product, marketing, operations, and engineering teams to identify automation opportunities.
• Translate business needs into technical solutions and ensure successful stakeholder adoption.
• Governance & Compliance
• Establish monitoring, auditing, and fallback mechanisms to ensure reliability and ethical use of AI.
• Define and enforce best practices around model versioning, data privacy, explainability, and human oversight.
• Innovation & Strategy
• Stay updated with the latest trends in generative AI, workflow orchestration, and MLops.
• Recommend emerging tools and platforms that align with strategic AI goals. Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, AI, Data Engineering, or related field.
• 5+ years of experience in software architecture, AI engineering, or automation design.
• Hands-on experience with AI / ML lifecycle tools (e.g., MLflow, LangChain, Hugging Face).
• Strong understanding of workflow orchestration systems (e.g., Apache Airflow, Kubernetes, Zapier, n8n).
• Familiarity with large language models (LLMs), computer vision, NLP, and multimodal AI applications.
• Proficiency in Python, APIs (REST / GraphQL), and cloud infrastructure (AWS, GCP, Azure). Preferred Qualifications
• Experience with RPA platforms (UiPath, Automation Anywhere) and enterprise integrations.
• Exposure to low-code / no-code automation platforms.
• Experience with prompt engineering and fine-tuning LLMs.
• Knowledge of data governance, security, and ethical AI principles. #LI-PT1