Hi, I’m Christian.
I build production multi-agent LLM systems and run systematic trading research under the same eval-first discipline. Two hats, one method.
As an AI Engineer: I design and operate multi-agent LLM platforms — orchestration, evaluation harnesses, model routing, structured-output contracts, RAG, and cost-aware deployment. Eleven-agent research platform with a 31-gate statistical eval harness, ~76,500 LOC of light-dependency Python, and tiered routing (Opus / Sonnet / Haiku / Fable) that keeps a multi-agent system economical to run continuously. AI Architecture curriculum authored from the ground up.
As a Quantitative Researcher: I read academic papers, build statistical models, write Python for backtesting, walk-forward validation, block-bootstrap CIs, and modern selection-bias statistics (Deflated Sharpe, PBO via CSCV, MinBTL). Prior Quant Researcher engagement on a 19V Capital systematic-strategy desk (5 asset classes, 31-gate filter).
Foundation:
PSHS-SMC (national competitive exam, 2022) (Nuclear Physics Major in Senior High)
USeP engineering units (calculus, physics, applied math)
UM Financial Management (current, 1st Sem AY 2026–27)
STA Certified Technical Analyst (Dec 2025)
102 professional certifications including NASA Space Apps (Galactic Problem Solver, Zurich CH) and Meta BIDA AIccelerate.
Open to AI Engineer, LLM Application Engineer, Quantitative Researcher, and Quant Trading roles. Remote, 20-30 hrs/wk, UTC+8.
Verified
