AI Foundation Architect

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Define scalable architectures for production AI and GenAI solutions, integrating models, agents, data platforms, enterprise applications, APIs, and cloud infrastructure.

• Establish architectural principles, reference designs, integration patterns, and technical standards for engineering teams.

• Document and make significant architecture decisions regarding cloud platforms, model integration, data access, security, scalability, performance, and cost.

• Review technical designs and guide engineering teams to ensure compliance with the established architecture and production requirements.

• Design secure and reliable AI foundations, incorporating identity management, access controls, monitoring, resilience, and human oversight.

• Collaborate with AI Engineers, Software Engineers, Data Engineers, and Governance specialists to ensure alignment of technical solutions across various domains.

• Engage directly with clients and technical stakeholders to comprehend requirements, elucidate architectural decisions, manage technical risks, and develop reusable architectural solutions.

• Balance business needs, technical requirements, and production constraints effectively.

• Clearly communicate technical decisions to clients and produce reusable architecture standards and documentation.

⛳️ Requirements

• 8+ years of experience in designing complex technical architectures, subject to local seniority verification.

• Extensive experience in guiding architecture for production enterprise applications and distributed systems.

• Practical experience in architecting production GenAI, LLM, or agentic solutions.

• Proven track record of making technical decisions across cloud infrastructure, applications, integrations, security, and operational systems.

• Experience in defining architecture standards, reference designs, technical requirements, and integration patterns.

• Excellent communication and consulting abilities, including experience collaborating with clients, engineering leaders, and technical stakeholders.

• Strong architectural expertise within at least one major cloud ecosystem, such as AWS, Azure, or GCP.

• Familiarity with enterprise AI services and model integration, including Amazon Bedrock, Azure AI, Vertex AI, OpenAI APIs, or similar platforms.

• Comprehensive knowledge of distributed systems, microservices, APIs, and enterprise integration architectures.

• Understanding of cloud security, identity and access management, scalability, resilience, and observability.

• Insight into data architectures, including Lakehouse, streaming, data platforms, and enterprise data integration.

• Familiarity with production AI architectures, encompassing RAG, AI agents, model access, tool integration, and human oversight.

• Experience in designing multi-agent systems, advanced RAG architectures, or multi-model AI solutions.

• Knowledge of MLOps, LLMOps, CI/CD, Kubernetes, Terraform, and infrastructure automation.

• Experience with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or similar technologies.

• Understanding of vector databases, AI gateways, event-driven architectures, or model-serving platforms.

• Familiarity with enterprise architecture frameworks, architecture reviews, or regulated environments.

• Experience in consulting or professional services, including conducting technical workshops and architecture assessments.

🏝️ Benefits

• Engage in international and multicultural projects.

• Opportunities to work with cutting-edge technologies within the Data, Cloud, and AI ecosystems.

• Access to training programs and ongoing professional development.

• Opportunities for professional growth and internal mobility.

• A culture that fosters collaboration, innovation, and continuous learning.