Phase 1: Remote (Weeks 1–3) — Foundations of AI-First Engineering
- AI-first development workflows (coding agents, MCP, real-time collaborative tooling)
- Retrieval-Augmented Generation (RAG), embedding techniques, and vector database usage
- Fast-paced project sprints emphasizing delivery within tight constraints
Phase 2: Onsite in Austin (Weeks 4–10) — Production AI at Scale
- Agent architectures, evaluation systems, verification methods, and observability tools (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-level execution: quality assurance, reliability engineering, and high-standard delivery
- Fine-tuning and deployment strategies (LoRA/QLoRA with production integration)
- Multi-agent strategies for modernizing existing real-world codebases
- Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)






