Agentic AI Solutions Architect - Remote, Latin America
Remote · Porto Alegre, Rio Grande do Sul, Brazil
Job Summary
Agentic AI Solutions Architect responsible for owning the technical vision for how clients use LLMs and agentic workflows, from discovery through production deployment. Lead client technical requests and advanced automation needs, design end-to-end agentic data and workflow architectures (data sources → automation platform / LLM → actions / dashboards), implement integrations and automation with tools like n8n, Make, Flowise, AWS Step Functions, custom APIs, and orchestration platforms (Airflow, Prefect, Temporal). Develop LLM applications for data enrichment, content generation, and data segmentation; collaborate with data engineering on MLOps and automation pipeline development; document solutions and patterns, and validate performance. Must have extensive experience in data warehousing (Snowflake, BigQuery), ETL/data integration, SQL, Python, AI/ML/LLM technologies, cloud platforms (AWS, GCP, Azure), and strong client-facing communication. The role emphasizes leadership in client discovery, presenting ROI-focused recommendations, and delivering end-to-end agentic architectures for automated marketing tasks and data quality checks.
Required Qualifications
- 5+ years of experience in technical roles focused on software engineering, data integration, or analytics
- Agency, consultancy, or client services background with a strong understanding of client delivery
- Deep hands-on experience with data warehousing platforms such as Snowflake and BigQuery
- Proficiency with ETL / data integration tools including Glue, AirByte, Python, and custom APIs
- Strong SQL skills and experience with data modeling
- Proficiency in Python for scripting, data manipulation, and deploying AI / ML models
- Proven experience working with AI / ML / LLM technologies in a data or workflow automation context
- Client-facing experience including leading discovery sessions, presenting solutions, and managing stakeholder expectations
- Familiarity with cloud platforms (AWS, GCP, or Azure) and their AI / ML services
- Understanding of Generative AI use cases and prompt engineering best practices
- Strong written and verbal communication skills in English
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