Ideal Experience Mix5+ 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.EducationDouble 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 SkillsLeadership and StrategyTechnology strategy and annual planningEngineering and AI team leadershipAgile project and resource managementTechnical recruitment, mentoring, and trainingProject budgeting, costing, pricing, and cash-flow forecastingEnterprise stakeholder and client managementInformation security and ISO 27001 complianceArtificial Intelligence and Machine LearningMachine-learning model development and production deploymentPredictive modelling, lead scoring, attribution, and collections optimizationGenerative AI and large language modelsVoice and WhatsApp AI agentsAI workflow and proposal-generation agentsModel training, validation, monitoring, and versioningExperiment tracking with MLflowTensorFlow, Keras, scikit-learn, OpenAI, Anthropic, Gemini, Grok, and OllamaSoftware EngineeringAdvanced PythonTypeScript and JavaScriptPHP, HTML, and CSSFastAPI, Flask, and DjangoREST APIs and backend system designAutomated testing with pytestSoftware-quality controls and SonarQube quality gatesMLOps, DevOps, and CloudCI/CD architecture and implementationGitHub Actions and Google Cloud BuildDocker and KubernetesArgo Workflows and Apache AirflowAWS and Google Cloud PlatformCloud-native ETL pipelinesModel deployment, monitoring, and production supportGrafana and PrometheusData and AnalyticsPostgreSQL, Redis, Supabase, and SASPower BI, Looker Studio, and data visualizationData ingestion and transformation pipelinesFinancial and operational reporting systemsAutomationn8n and MakeCron jobs, event triggers, and workflow orchestrationHybrid low-code and custom-developed automation systemsKey ResponsibilitiesDefine 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.

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Senior Data Engineer