Phase 1: Remote (Weeks 1–3) — Foundations of AI-First Engineering
- AI-native development workflows, including coding agents, MCP, and real-time collaboration tools
- Retrieval-Augmented Generation (RAG), vector databases, and embeddings
- Fast-paced project sprints centered on shipping under tight constraints
Phase 2: Onsite in Austin (Weeks 4–10) — Scaling Production AI
- Agent architectures, evaluation frameworks, verification methods, and observability tools (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-grade delivery standards: quality assurance, system reliability, and high-rigor execution
- Fine-tuning and deployment strategies (LoRA/QLoRA and production integration)
- Multi-agent modernization applied to existing, real-world codebases
- Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)






