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.