AWS Data & AI Solution Architect – LATAM

Overview We are looking for a senior AWS Data & AI Architect to lead front-end technical solutioning for AI & Data opportunities across the LATAM region. The architect will work closely with regional sales, presales, delivery, and customer stakeholders to understand business requirements, shape solution approaches, lead technical discussions, and support PoCs and proposal development. Responsibilities Lead technical discovery and solutioning discussions with customers Translate business requirements into scalable AWS Data and AI architectures Define solution architecture, technology stack, integration approach, security, and deployment model Develop architecture diagrams, solution documents, effort estimates, assumptions, dependencies, and technical proposals Lead or support PoCs, technical demonstrations, and solution validation exercises Collaborate with sales and bid teams during RFP/RFI responses and proposal development Provide technical guidance to delivery teams during project initiation and transition Present solutions confidently to customer architects, engineering teams, and senior stakeholders Identify reusable solution patterns and accelerators for the LATAM AI & Data portfolio Travel to customer locations within the LATAM region when required Requirements Strong expertise in AWS Data and Analytics services, including S3, Glue, Redshift, EMR, Athena, Lake Formation, Kinesis, Lambda, RDS, DynamoDB, Step Functions, QuickSight, IAM, and CloudWatch. Strong Python programming skills for data engineering, automation, APIs, analytics, and AI/ML use cases. Experience designing modern data platforms, data lakes, lakehouse solutions, ETL/ELT pipelines, data governance, data quality, and analytics architectures. Hands-on experience with Amazon Bedrock, foundation models, Knowledge Bases, Guardrails, Agents, and Generative AI solution patterns. Good understanding of Agentic AI, multi-agent orchestration, RAG, vector databases, prompt engineering, and LLM evaluation. Experience designing secure, scalable, resilient, and cost-optimized AWS architectures. Knowledge of APIs, microservices, event-driven architectures, and enterprise integration patterns. Ability to estimate delivery effort, infrastructure requirements, and AWS consumption costs.

Lead technical discovery and solutioning discussions with customers Translate business requirements into scalable AWS Data and AI architectures Define solution architecture, technology stack, integration approach, security, and deployment model Develop architecture diagrams, solution documents, effort estimates, assumptions, dependencies, and technical proposals Lead or support PoCs, technical demonstrations, and solution validation exercises Collaborate with sales and bid teams during RFP/RFI responses and proposal development Provide technical guidance to delivery teams during project initiation and transition Present solutions confidently to customer architects, engineering teams, and senior stakeholders Identify reusable solution patterns and accelerators for the LATAM AI & Data portfolio Travel to customer locations within the LATAM region when required

Strong expertise in AWS Data and Analytics services, including S3, Glue, Redshift, EMR, Athena, Lake Formation, Kinesis, Lambda, RDS, DynamoDB, Step Functions, QuickSight, IAM, and CloudWatch. Strong Python programming skills for data engineering, automation, APIs, analytics, and AI/ML use cases. Experience designing modern data platforms, data lakes, lakehouse solutions, ETL/ELT pipelines, data governance, data quality, and analytics architectures. Hands-on experience with Amazon Bedrock, foundation models, Knowledge Bases, Guardrails, Agents, and Generative AI solution patterns. Good understanding of Agentic AI, multi-agent orchestration, RAG, vector databases, prompt engineering, and LLM evaluation. Experience designing secure, scalable, resilient, and cost-optimized AWS architectures. Knowledge of APIs, microservices, event-driven architectures, and enterprise integration patterns. Ability to estimate delivery effort, infrastructure requirements, and AWS consumption costs.