Key Responsibilities

• Backend EngineeringWrite, review and understand well-structured, tested, production-quality code, stepping in with your own judgement where agentic coding tools fall short
• Build and maintain production-grade backend services that serve and process AutoGrab's live data
• Work across a variety of databases, SQL and data-intensive applications, both stream and batch oriented

• Agentic AI EngineeringDesign, build and operate agentic LLM workflows and data applications in production
• Apply prompt engineering, RAG and vector search, and tool/function calling in a data pipeline or data analysis context
• Own LLM evaluation and observability, and manage inference scalably, reliably and cost-effectively
• Contribute to guardrail design and compliance-sensitive flow handling within AutoGrab's AI systems

• Infrastructure & OperationsDeploy and operate LLM-related services on GCP, including Vertex AI, Cloud SQL and Cloud Run/GKE
• Work with infrastructure-as-code (Terraform) and CI/CD pipelines to maintain operational discipline
• Contribute to system reliability, cost management and observability across production services

• Collaboration & CommunicationWork through ambiguity with the team and technical leadership, making trade-offs clearly and setting expectations honestly
• Collaborate closely with engineers across backend, data science and product disciplines
• Contribute to engineering discipline: code review, testing standards and technical documentation