AI Foundation Architect

🔥 1 hour ago

🇨🇴 Colombia – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🤖 Artificial Intelligence

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Keyrus

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1996

🤝 B2B

💼 Consulting

B2B • Data Analytics • Consulting

Keyrus is an international company passionate about leveraging data to make impactful changes in life, society, and the future. With a presence in 18 countries, Keyrus is dedicated to creating meaningful careers for its employees by fostering excellence, trust, creativity, kindness, and fun. Specializing in data analytics, data advisory, and management, Keyrus provides vendor-agnostic solutions and continuous training opportunities through its KLX platform. The company also emphasizes a healthy work-life balance with a range of benefits, including sports events, healthcare plans, and an inclusive work culture. Keyrus is committed to openness and transparency to maintain positive workplace relationships and is driven to innovate and influence the digital future.

📋 Description

• Define scalable architectures for production AI and GenAI solutions, connecting models, agents, data platforms, enterprise applications, APIs, and cloud infrastructure • Establish architecture principles, reference designs, integration patterns, and technical standards for engineering teams • Make and document key architecture decisions involving cloud platforms, model integration, data access, security, scalability, performance, and cost • Review technical designs and guide engineering teams to ensure solutions follow the agreed architecture and production requirements • Design secure and reliable AI foundations, including identity management, access controls, monitoring, resilience, and human oversight • Collaborate with AI Engineers, Software Engineers, Data Engineers, and Governance specialists to align technical solutions across different areas • Work directly with clients and technical stakeholders to understand requirements, explain architecture decisions, manage technical risks, and develop reusable architecture solutions • Balance business needs, technical requirements, and production constraints • Communicate technical decisions clearly to clients and create reusable architecture standards and documentation

🎯 Requirements

• 8+ years of experience designing complex technical architectures, subject to local seniority confirmation • Strong experience designing and guiding architecture for production enterprise applications and distributed systems • Practical experience architecting production GenAI, LLM, or agentic solutions • Experience making technical decisions across cloud infrastructure, applications, integrations, security, and operational systems • Experience defining architecture standards, reference designs, technical requirements, and integration patterns • Strong communication and consulting skills, including experience working with clients, engineering leaders, and technical stakeholders • Strong architecture expertise in at least one major cloud ecosystem, such as AWS, Azure, or GCP • Experience with enterprise AI services and model integration, such as Amazon Bedrock, Azure AI, Vertex AI, OpenAI APIs, or comparable platforms • Strong knowledge of distributed systems, microservices, APIs, and enterprise integration architectures • Understanding of cloud security, identity and access management, scalability, resilience, and observability • Knowledge of data architectures, including Lakehouse, streaming, data platforms, and enterprise data integration • Understanding of production AI architectures, including RAG, AI agents, model access, tool integration, and human oversight • Experience 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 comparable technologies • Familiarity with vector databases, AI gateways, event-driven architectures, or model-serving platforms • Experience with enterprise architecture frameworks, architecture reviews, or regulated environments • Experience in consulting or professional services, including technical workshops and architecture assessments

🏖️ Benefits

• International and multicultural projects • Opportunities to work with leading technologies in Data, Cloud, and AI ecosystems • Access to training programs and continuous professional development • Professional growth opportunities and internal mobility • A culture built on collaboration, innovation, and continuous learning