Phase 1: Remote (Weeks 1–3) — Foundations in AI-First Engineering
- AI-first development practices (coding agents, MCP, real-time collaboration)
- Retrieval-Augmented Generation (RAG), embeddings, and vector database systems
- Fast-paced project sprints emphasizing delivery under constraints
Phase 2: Onsite in Austin (Weeks 4–10) — Production-Scale AI Engineering
- Agent architectures, evaluations, verification, and observability tools (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-standard delivery: quality assurance, reliability, and rigorous execution
- Fine-tuning and deployment methodologies (LoRA/QLoRA + production integration)
- Multi-agent strategies for modernizing real-world codebases
- Multimodal AI applications (image/video/voice) and scalable cloud infrastructure (AWS/Azure)






