Idóneo Experience Mix

- 5+ years leading technology strategy, engineering teams, and AI product delivery.
- 6+ years designing and deploying production-grade AI and machine-learning solutions.
- 5+ years with cloud platforms, DevOps, CI/CD, containerization, and data pipelines.
- Experience managing multidisciplinary teams of up to 10 people.
- Proven delivery of AI solutions within banking, financial services, healthcare, insurance, or real estate.
- Experience working directly with enterprise customers and senior stakeholders.
- Startup, co-founder, CTO, or technology-department-building experience is strongly preferred.

Education

- Double Degree in Mathematics and Computer Science, or an equivalent degree in Computer Science, Mathematics, Artificial Intelligence, Data Science, Engineering, or a closely related quantitative field.
- Strong academic record preferred.
- Professional fluency in English and Spanish.

Core Skills

Leadership and Strategy

- Technology strategy and annual planning
- Engineering and AI team leadership
- Agile project and resource management
- Technical recruitment, mentoring, and training
- Project budgeting, costing, pricing, and cash-flow forecasting
- Enterprise stakeholder and client management
- Information security and ISO 27001 compliance

Artificial Intelligence and Machine Learning

- Machine-learning model development and production deployment
- Predictive modelling, lead scoring, attribution, and collections optimization
- Generative AI and large language models
- Voice and WhatsApp AI agents
- AI workflow and proposal-generation agents
- Model training, validation, monitoring, and versioning
- Experiment tracking with MLflow
- TensorFlow, Keras, scikit-learn, OpenAI, Anthropic, Gemini, Grok, and Ollama

Software Engineering

- Advanced Python
- TypeScript and JavaScript
- PHP, HTML, and CSS
- FastAPI, Flask, and Django
- REST APIs and backend system design
- Automated testing with pytest




- Software-quality controls and SonarQube quality gates

MLOps, DevOps, and Cloud

- CI/CD architecture and implementation
- GitHub Actions and Google Cloud Build
- Docker and Kubernetes
- Argo Workflows and Apache Airflow
- AWS and Google Cloud Platform
- Cloud-native ETL pipelines
- Model deployment, monitoring, and production support
- Grafana and Prometheus

Data and Analytics

- PostgreSQL, Redis, Supabase, and SAS
- Power BI, Looker Studio, and data visualization
- Data ingestion and transformation pipelines
- Financial and operational reporting systems

Automation

- n8n and Make
- Cron jobs, event triggers, and workflow orchestration
- Hybrid low-code and custom-developed automation systems

Key Responsibilities

- Define and implement the annual technology roadmap in alignment with business objectives.
- Lead AI, machine-learning, software-engineering, data, DevOps, and MLOps initiatives.
- Design and deploy production AI solutions for enterprise customers.
- Develop predictive models, generative-AI applications, conversational agents, and intelligent automation systems.
- Establish scalable model-training, experiment-tracking, deployment, monitoring, and retraining processes.
- Design and maintain cloud-native architectures across AWS and GCP.
- Implement CI/CD pipelines, automated testing, code-quality controls, and secure development practices.
- Lead multidisciplinary teams using agile methodologies.
- Recruit, train, mentor, and develop technical talent.
- Prepare project plans covering scope, resources, timelines, costs, risks, and commercial pricing.
- Manage technical relationships with enterprise customers and communicate complex solutions to non-technical stakeholders.
- Ensure compliance with ISO 27001 and information-security requirements throughout the AI development lifecycle.
- Build internal systems for financial tracking, operational reporting, workflow automation, and proposal generation.
- Evaluate emerging AI technologies and determine their suitability for customer and internal applications.

📌 Senior Data Engineer (Madrid)
🏢 Encardio Rite
📍 Madrid