Responsibilities
- Develop deep technical enablement programs based off of Forward Deployed Engineer and Cloud AI CE requirements for learning of AI products.
- Map persona-based views of technical GTM field enablement needs, leading the development of curriculum for in-person, e-learning and other assets.
- Design, build and execute structured AI product deep technical training and enablement programs, and build-out of materials for P0, P1 and other priority AI initiatives.
- Integrate into technical sales teams to understand enablement needs and become a trusted advisor to technical AI leadership.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with software development using Python or similar coding languages.
- Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
- Experience building pipelines for structured and unstructured data using both vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise AI solutions.
- Experience leading technical discovery sessions.
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, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.