Artificial Intelligence

• Run long-term client programs across Experience Intelligence and Operational Intelligence areas
• Lead discovery across customer experience, marketing operations, forecasting, and inventory
• Benchmark client business performance and identify opportunities
• Build the business case for scoped work, including expected impact, delivery cost, and measurement
• Write precise specifications for engineers and analysts
• Direct delivery across concurrent projects
• Drive adoption after systems launch
• Serve as the primary point of contact for accounts
• Run accounts independently and involve the AI Practices Lead for notable conversations or key decisions
• Develop client relationships, identify expansion opportunities, and remain accountable for business outcomes

AI Strategist

• Translate authentic Earth-science workflows into self-contained terminal-based benchmark tasks.
• Prepare and structure geospatial, climate, atmospheric, geological, hydrological, or oceanographic datasets.
• Build reproducible computational environments using scientific libraries and command-line tools.
• Develop expert reference solutions using Python, R, Bash, Julia, or domain-specific software.
• Design tasks involving geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, and environmental risk analysis.
• Define objective grading criteria for scientific outputs, data transformations, and spatial or temporal accuracy.
• Validate coordinate systems, units, timestamps, missing-data handling, and scientific assumptions.
• Create automated tests for numerical tolerances, file formats, metadata, and reproducibility.
• Debug issues involving projections, large datasets, dependencies, performance, and numerical stability.
• Document data provenance, expected outputs, edge cases, assumptions, and limitations.

Earth & Environmental Science Expert – AI Projects

• Lead the enterprise AI Delivery Engineering organization
• Build and scale a high-performing team of AI Engineers, AI Solution Architects, and AI Operations professionals
• Establish delivery standards, engineering practices, and operating models for AI solution development
• Own execution across multiple concurrent AI programs and business domains
• Lead delivery of AI agents, agentic workflows, AI-powered business automations, conversational AI, knowledge assistants, RAG solutions, and multi-agent orchestration
• Ensure AI solutions are secure, scalable, maintainable, and reusable
• Establish standards for prompt engineering, agent development, tool integration, MCP implementation, API integrations, workflow orchestration, code quality, reusable frameworks, and secure development
• Drive adoption of reusable AI components and engineering accelerators
• Own capacity planning, prioritization, roadmaps, resource allocation, milestone management, executive reporting, risk management, and delivery metrics
• Oversee production monitoring, agent health, incident management, performance and cost optimization, model and prompt optimization, and AI observability
• Create and manage the AI Governance council with Security and Compliance teams
• Ensure responsible AI, security reviews, privacy compliance, human-in-the-loop controls, auditability, model governance, risk assessments, and regulatory compliance
• Partner with AI Strategy, Enterprise Architecture, Business Systems, Data & Analytics, Security, Product Owners, Legal, Procurement, and vendor partners
• Manage delivery budgets, vendor performance, delivery costs, AI platform optimization, FinOps metrics, ROI, and engineering capacity
• Build a world-class AI delivery organization through talent development, workforce planning, coaching, mentoring, organizational design, hiring, performance management, engineering culture, and innovation

Senior Director – AI Delivery

• Define and lead the multi-year product vision for the payments ecosystem
• Identify major new product opportunities in the payments landscape
• Drive strategic direction across multiple product pillars and initiatives
• Align product strategy with company growth, revenue objectives, and market expansion
• Lead and develop a team of Product Managers
• Define team structure, hiring plans, and career development for product leaders
• Establish product management standards and operating processes
• Foster ownership, accountability, and innovation
• Drive the evolution of the payments orchestration platform and capabilities layer
• Ensure support for payment connectivity, orchestration, reconciliation, financial operations, subscriptions, recurring payments, disputes, and chargebacks
• Ensure architecture supports enterprise-scale merchants and high transaction volumes
• Partner with Engineering leadership on scalable technical architecture
• Work with Sales, Customer Success, and Partnerships to translate market needs into product strategy
• Remove organizational blockers and drive cross-team alignment
• Lead initiatives spanning multiple product areas
• Own business performance of the payments product area
• Define success metrics and product KPIs tied to growth, merchant adoption, and platform performance
• Balance customer value, scalability, and business outcomes in product decisions
• Evaluate emerging payments trends
• Identify opportunities in orchestration, approval optimization, financial automation, and AI-driven payment intelligence
• Position the platform as a leader in enterprise payments infrastructure

Product Head, AI

• Use ChatGPT, Claude, and other AI tools daily for research, content creation, creative development, analysis, and marketing operations
• Create and repurpose content for LinkedIn and other social media channels, including posts, graphics, carousels, and short-form content
• Create AI-generated images, videos, and other visual content using modern AI creative tools
• Develop and improve articles, case studies, newsletters, presentations, one-pagers, landing pages, and other marketing assets
• Implement GEO and AEO strategies to improve Azumo’s visibility in AI-powered search platforms such as ChatGPT, Claude, Gemini, and Perplexity
• Monitor how Azumo and its competitors appear across traditional and AI search, identify content gaps, and turn those insights into actionable content improvements
• Use AI and analytics tools to build recurring reports covering traffic, social media, campaigns, leads, conversions, AI search visibility, and other relevant marketing KPIs
• Identify opportunities to automate repetitive marketing tasks and improve existing workflows
• Help maintain and update Azumo’s website when needed
• Support other marketing initiatives in collaboration with the marketing, sales, and leadership teams

AI-Powered Marketing Specialist

• Design complex scientific workflows across computational life sciences that require multiple analytical and computational steps.
• Develop realistic scientific datasets, input files, instructions, constraints, and expected deliverables.
• Create tasks requiring AI agents to inspect data, select appropriate methods, execute analyses, and troubleshoot intermediate results.
• Implement reproducible expert solutions and objectively verifiable ground truths.
• Design robust automated or semi-automated grading criteria for scientific tasks.
• Validate scientific assumptions, calculations, code, intermediate outputs, and final results.
• Ensure task dependencies, data, and computational resources can be reliably packaged in controlled environments.
• Develop workflows using Python, command-line tools, scientific libraries, and relevant domain-specific software.
• Ensure tasks assess scientific reasoning and execution rather than memorization.
• Maintain high task quality and throughput while incorporating reviewer feedback.

Computational Biology, AI Specialist

• Diseñar e implementar el Centro de Excelencia de IA
• Diseñar e implementar el modelo de gobierno sobre cómo se construye, compra y usa la IA en la compañía y en proyectos de clientes
• Definir arquitecturas de referencia, estándares de LLMOps/MLOps y criterios de evaluación de sistemas de IA
• Evaluar sistemas de IA frente a sesgo, alucinación y fuga de datos
• Aportar criterio técnico y de riesgo a propuestas de IA para clientes
• Construir aceleradores y activos reutilizables
• Liderar la red de equipos del clúster de IA y definir roles y habilidades
• Conducir el programa de alfabetización en IA de la organización

Líder de Inteligência Artificial

• Diseñar, desplegar y operar soluciones de ML e IA generativa en Google Cloud Vertex AI
• Implementar motores de recomendación, búsqueda semántica y clasificación automática de contenidos
• Desarrollar pipelines de metadatos y analítica sobre el catálogo de contenidos y usuarios
• Entrenar y poner en producción modelos de aprendizaje automático y LLMs
• Implementar prácticas de MLOps: versionado, monitoreo y reentrenamiento de modelos
• Colaborar con equipos de producto y datos para priorizar casos de uso de IA
• Documentar decisiones técnicas y transferir conocimiento al equipo interno
• Monitorear y optimizar costos de cómputo e inferencia en Vertex AI

Ingeniero/a de IA – Google Cloud Vertex AI, Part-Time

• Investigate legacy applications, scripts, and manual processes to understand their purpose, dependencies, and actual behavior
• Document system behavior and maintain a knowledge base
• Decide whether capabilities should be kept, replaced, consolidated, automated, or retired
• Create and maintain a prioritized modernization roadmap aligned with business priorities and deadlines
• Coordinate initiatives from discovery through release and handover
• Collaborate across engineering, QA, Operations, business stakeholders, the managed service provider, and outside partners
• Ensure shipped work has requirements, documentation, monitoring, and an accountable owner
• Track material risks through resolution
• Convert recurring manual work into reusable AI-assisted workflows for discovery, documentation, planning, and risk tracking

AI Modernization Manager

• Design, configure, and deploy end-to-end conversational AI (IVR / IVA) solutions on the Omilia OCP platform
• Build agentic workflows blended with traditional NLU modelling and omnichannel integrations
• Integrate GenAI capabilities into production deployments, including RAG pipelines, embedding search, and LLM prompt engineering
• Manage contact centre infrastructure integrations including IVR, SIP, CTI, and omnichannel APIs
• Own technical delivery quality from design through go-live and hypercare
• Serve as the primary technical point of contact for assigned client engagements
• Translate business requirements into technical architectures and CX designs
• Maintain trusted relationships with customers and partners throughout the project lifecycle
• Identify and manage delivery risks, escalate complex technical issues, and drive resolution
• Provide technical guidance and mentorship to junior engineers
• Contribute to delivery accelerators, tooling, reusable solution components, and best-practice documentation
• Research conversational AI, agentic frameworks, and GenAI tooling
• Collaborate across Solution Delivery, Product, Platform, R&D, Sales, Pre-Sales, and Certified Partners

Artificial Intelligence jobs in Colombia