Senior AI/Data Engineer (Google Cloud, Agentic AI) - Part-time - NA/LATAM/EU

Job title RedwoodAI MVP Co-creator

About the Project

RedwoodAI is building an adaptive resilience and due diligence model for data centers, focused on economic, environmental, and infrastructure performance across energy, power, water, climate, and natural resources.
The next phase is to evolve that prototype into a demonstration-grade MVP suitable for investor and partner engagement.

The model is geocentric and science-driven, integrating multiple real-world data sources (energy, weather, water, climate, critical minerals) and orchestrating them through an agentic AI architecture using Google Cloud and Gemini / DeepMind tooling.

This is not a “build-to-spec” role. The ideal engineer is intellectually curious, enjoys learning new domains, and collaborates deeply on concept + architecture, not just code.

What You’ll Be Working On

• Expanding an existing Google Cloud–based prototype into a robust demo/MVP
• Designing and implementing agentic AI workflows across multiple domains (energy, water, climate, resources)
• Integrating external data sources (APIs, structured & unstructured data)
• Working with Google AI / DeepMind APIs (Gemini, Vertex AI)
• Developing retrieval, inference, and orchestration logic (RAG and beyond)
• Collaborating directly with the founder on:
• Model architecture decisions
• Data strategy and sourcing
• Iterative experimentation and refinement
• Supporting a functional MVP UI (already exists) rather than building a full product from scratch

Required Skills & Experience

Technical

• Strong Python development experience
• Solid working knowledge of Google Cloud Platform (GCP) - Vertex AI, Cloud Functions / Cloud Run, Logging, monitoring, pipelines
• Experience integrating AI foundation models via APIs
• Strong background in: Data ingestion & integration, APIs (external data sources), Databases and retrieval systems
• Familiarity with: RAG architectures, Agentic AI concepts (multi-agent systems, orchestration)
• Ability to reason about model architecture, not just implementation

Ideal Candidate

• Intellectually curious and eager to learn
• Enjoys collaborating on concepts, not just executing specs
• Comfortable working in an evolving, founder-led environment

Nice-to-Have (Not Required)

• Background in hard sciences, engineering, climate, energy, or infrastructure
• Experience with geospatial, weather, or environmental datasets
• Exposure to investor-facing demos or MVPs
• Experience working closely with founders on early-stage products