Phase 1: Remote Period (Weeks 1–3) — Foundations of AI-First Engineering
- Development workflows centered on AI tooling (coding agents, Model Context Protocol, real-time collaborative systems)
- Retrieval-Augmented Generation (RAG) techniques, embedding models, and vector database implementations
- Accelerated project cycles emphasizing delivery under resource and time constraints
Phase 2: Onsite Period in Austin (Weeks 4–10) — Production-Scale AI Systems
- Agent architectures, evaluation frameworks, verification methods, and observability tools (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-standard delivery practices: quality assurance, system reliability, and high-expectation execution
- Model fine-tuning and deployment strategies (LoRA/QLoRA + production-ready integration)
- Multi-agent approaches to modernizing legacy systems and existing codebases
- Multimodal AI implementations (image/video/voice processing) and scalable cloud infrastructure (AWS/Azure)






