Agentic AI Solutions Architect - Remote, Latin America
Remote · San Luis Potosí, San Luis Potosí, Mexico
Job Summary
Agentic AI Solutions Architect sits at the intersection of client strategy, data engineering, and applied AI. Own the technical vision for how clients use LLMs and agentic workflows to transform operations—from first discovery conversation to production deployment. Split time between being a trusted technical advisor to client stakeholders and designing and shipping end-to-end agentic architectures that deliver measurable ROI. Lead client discovery sessions to identify high-leverage AI opportunities; design integrated data and AI architectures connecting marketing platforms to data warehouses and LLM services; implement integrations and automation using tools like n8n, Make, Flowise, AWS Step Functions, custom APIs, and orchestration platforms (Airflow, Prefect, Temporal); design and deploy agentic workflows for automated marketing tasks, data quality checks, and predictive analytics; develop and fine-tune LLM applications for data enrichment, content generation, and data segmentation; collaborate with data engineering teams on MLOps and automation pipeline development; document architectures and best practices; test and validate AI-driven outputs.
Required Qualifications
- 5+ years 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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