Cloud Data Migration Engineer (AI Systems)

About Us Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. Role overview Our client is a globally recognized AI research and engineering organization working at the forefront of large language models and advanced AI systems. They partner with leading enterprises and frontier AI labs to build scalable, high-performance AI solutions that deliver real-world impact. We are hiring a Cloud Data Migration & AI Systems Engineer for a 6 months contract opportunity. In this role, you will work closely with researchers and engineering teams to design, execute, and validate data migration workflows across cloud platforms, while integrating and evaluating LLM/Generative AI components within these systems. This is a high-impact role combining cloud engineering, data systems, and AI evaluation in a cutting-edge environment.

Commitments Required: 8 hours per day with an overlap of 8 hours with PST. Employment type: Contractor assignment (no medical/paid leave) Duration of contract: 6+ months Location: LATAM Interview: 15 min AI-led interview

Your Daily Responsibilities• Design and execute data migration workflows across cloud platforms (AWS, GCP, Azure) • Define and optimize migration strategies (online vs offline, scalability, performance trade-offs) • Build and maintain data pipelines and ETL/ELT workflows in distributed systems • Integrate and evaluate LLM / Generative AI components within workflows • Perform system testing and validation, including: • Executing test scenarios • Identifying edge cases and failure points • Debugging and analyzing system behavior

• Ensure data integrity, consistency, and performance across systems • Document findings, insights, and technical recommendations • Collaborate with cross-functional teams (engineering, data, product, research)