Minimum qualifications:
Bachelor’s degree in engineering, computer science, a related field, or equivalent practical experience.
3 years of experience in building and shipping production-grade AI-driven solutions to external or internal customers using Python, TypeScript, or similar languages.
Experience managing technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
Experience building pipelines for structured and unstructured data, incorporating vector databases and retrieval-augmented generation (RAG) architectures.
Preferred qualifications:
Master’s degree or PhD in AI, computer science, or a related technical field.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation.
Knowledge of LLM-native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.