37-Month GenAI-First Career Transformation
Business Ops β GenAI-First Data Analyst & AI Engineer β GenAI Data Engineer + AI Systems β ML Engineer + Local LLM Specialist β Agentic AI Engineer β Senior LLM Engineer
While most candidates learn traditional tools only, this journey integrates GenAI/LLM engineering systematically from Week 1βbuilding production AI systems with LLM SDKs (Gemini, OpenAI, Claude), RAG pipelines, Multimodal AI, and Streamlit by Month 1. Progressing through Vector DBs, local LLMs, to MCP + multi-agent orchestration by Month 34.
1099 Reconciliation ETL Pipeline: Live system at Daybright Financial
Status: Active (Months 1-5)
Focus: Python, SQL + LLM SDKs + RAG + Multimodal AI + Streamlit
Goal: AI Engineer who knows Analytics
Timeline: Months 6-15
Focus: AWS + Vector DBs + RAG Infrastructure
Timeline: Months 16-29
Focus: ML + Ollama + Fine-Tuning (PEFT)
Timeline: Months 30-34
Focus: MCP + LangGraph + Multi-Agent Systems
Timeline: Months 35-37
Focus: LLMOps Evaluation + Production AI
Each project introduces new skills that build on the previous
Production system automating retirement plan distribution reconciliation between enterprise financial systems.
π° $15K+ annual savings β’ β‘ 95% time reduction β’ π Zero errors since deployment
Python β’ pandas β’ openpyxl β’ pytest β’ GitHub Actions CI
Foundation: ETL + Testing + CI/CDAI-Powered PII-Safe Data Intelligence: Natural language analytics for retirement plan operations with PII protection and AI guardrails.
π€ LLM SDK (provider-agnostic) + PandasAI + Pydantic structured outputs + PII guardrails
+ LLM SDK + Streamlit + Pydantic + PII HandlingAI-Powered HR Policy Chatbot: RAG chatbot answering policy questions with cited sources. Auto-escalates to HR when uncertain.
π§ Embeddings + ChromaDB + Semantic Search + RAG Pipeline + Ticket Escalation
+ Embeddings + ChromaDB + RAG + Semantic SearchAI-Powered Distribution Form Validator: Multimodal AI reads retirement plan forms (handwritten checkboxes, signatures), validates, and routes.
ποΈ Gemini Vision SDK + Multimodal AI + Business Rule Validation + Email Automation
+ Multimodal AI (Vision LLM) + Document ProcessingAI-Powered Workflow Demand Analysis: 8+ months of OnBase enterprise data enabling data-driven staffing decisions.
π€ LLM SDK + PandasAI + Plotly + Real production data + Privacy guardrails
π― 8+ months enterprise data β’ π Distribution vs Loan segmentation β’ π¬ AI chat interface
+ Enterprise Real Data + Advanced AnalyticsAI-Powered Streaming Subscription Advisor: Optimizes household streaming spend through AI rotation planning, content search, and savings forecasting.
πΊ Watchmode/TMDB APIs + httpx async + AI Rotation Planner + Cost Analytics
+ External APIs + Consumer UX + Optimization EngineAI-Powered Predictive Trigger Analysis: Defensible research system for small-cap stocks with statistical rigor. Evolves through all 5 career stages.
π¬ SEC Form 4 + Wikipedia + News + DuckDB Lakehouse + Walk-Forward Validation
π 5 trigger types β’ π― Statistical methodology β’ ποΈ Complete LLM career demonstration
+ Statistical Methodology + DuckDB + Async + Multi-Source