Phase 1: Remote (Weeks 1–3) — Foundations in AI-First Engineering
- Development workflows centered on AI (coding agents, MCP, real-time collaboration)
- Retrieval-Augmented Generation (RAG), embeddings, and vector database technologies
- Accelerated project sprints emphasizing delivery under constraints
Phase 2: Onsite in Austin (Weeks 4–10) — Production-Scale AI Systems
- Agent architectures, evaluations, verification, and observability tooling (LangChain/LangSmith/LangFuse/CrewAI)
- Enterprise-level delivery practices: QA, reliability, and high-standards execution
- Fine-tuning and deployment strategies (LoRA/QLoRA with production integration)
- Multi-agent modernization applied to real-world codebases
- Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)





