Phase 1: Remote (Weeks 1–3) — Foundations in AI-First Engineering
- AI-native development workflows (coding agents, MCP, real-time collaborative tooling)
- Retrieval-Augmented Generation (RAG), embeddings, and vector database integration
- High-velocity project sprints emphasizing delivery under tight constraints
Phase 2: Onsite in Austin (Weeks 4–10) — Production-Scale AI Systems
- Agent architectures, evaluation frameworks, verification, and observability tooling (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-level delivery standards: quality assurance, system reliability, and rigorous execution
- Fine-tuning techniques + deployment strategies (LoRA/QLoRA + production-ready integration)
- Multi-agent transformation of legacy and real-world codebases
- Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)






