AI Engineer

• Review requirements with the FDE, assess technical feasibility, estimate implementation effort and identify dependencies.
• Develop AI agents, LLM workflows and retrieval-augmented generation solutions for approved business use cases.
• Build backend services and APIs, and integrate client applications, databases and approved data sources.
• Implement data ingestion, document processing, embeddings and retrieval, respecting client data permissions.
• Evaluate accuracy, reliability, latency and usage cost; test failure cases and improve solution quality.
• Apply approved access controls, secure credential handling and client data protection practices.
• Deploy solutions in the agreed cloud, on-premises or hybrid environment, and implement monitoring and operational support procedures.
• Support demonstrations, client acceptance testing and go-live; resolve defects and maintain technical documentation.
• Escalate technical risks and blockers to CTO and follow approved architecture, quality and release decisions.