AI ENGINEER · THE HAGUE, NL

Building AI that
earns its place
in the real world.

I’m Nicholai. I turn emerging AI capabilities into useful systems, with an eye for evidence, reliability, and the people who use them.

01 / LLM systems & agents02 / Evaluation & RAG03 / Cloud delivery
01 / SELECTED WORK

Proof in the building.

Explore two live research apps, then the supporting work in agents, evaluation, and cloud delivery.

INFERNOMICS LIVE APP / 001
LATENCY / COST / COMPLETIONTrade-offs,
made visible.
OUTPUT TOKENS →
LLM EVALUATION2026

Infernomics

Inspect 60 archived inference attempts for one model across three output limits. Compare completion, measured latency, token use, and estimated cost.

ReactTypeScriptCloudflare Pages
ECONOMIC INTELLIGENCE LIVE APP / 002
WORLD BANK DATA ↔ DATED SOURCES ↔ PDF
ECONOMIC DATA WORKSPACE2026

Global Economic Intelligence

Explore sourced World Bank indicators, compare five economies, inspect deterministic analysis and dated report context, and export the displayed briefing as a PDF.

ReactWorld BankCloudflare
RETAIL SUPPORT AGENT / 003
CONVERSATION, GROUNDED IN ACTION
CONVERSATIONAL AI2026

Retail Support AgentOps

A Rasa prototype that checks simulated order data before giving support guidance, with deliberate fallback and human handoff paths.

RasaFastAPITesting
↗
CHIPSCOPE MCP / 004
EXPLICIT TOOLS · INSPECTABLE CONTEXT
AGENT TOOLING2026

ChipScope MCP

A small MCP server exposing semiconductor context through named tools and resources, with a rule-based baseline and paired LLM evaluation.

MCPPythonEvaluation
↗
CLOUD ENGINEERING DEPLOY / 005
FROM LOCAL API TO LIVE SERVICE
CLOUD & INFRASTRUCTURE2026

Cloud Engineering API

A live FastAPI service on AWS EC2, with Docker, Nginx, HTTPS, GitHub Actions, and a separate Terraform networking lab.

AWSTerraformCI/CD
↗
REVIEW INTELLIGENCE NLP / 006
CLASSIFY · CLUSTER · SUMMARIZE
APPLIED NLP2025

Product Review Analyzer

An end-to-end review pipeline combining a fine-tuned DeBERTa sentiment model, topic clustering, and BART summaries in a Gradio interface.

TransformersDeBERTaGradio
↗
More experiments on GitHub
02 / HOW I THINK

Curiosity with discipline.

The technology changes quickly. The engineering habits that make it useful matter even more.

01 —
◎

Start with the problem

Understand the workflow and its constraints before choosing a model, agent, or architecture.

02 —
⌁

Make claims testable

Use baselines, evaluation sets, and clear limitations to learn what actually works.

03 —
↗

Ship the whole system

Connect models to data, APIs, interfaces, deployment, and the people relying on them.

03 / THE PERSON BEHIND THE CODE

A builder who
keeps learning.

My path into AI came through years of leading teams and improving real operations. That experience shaped how I build: practical first, thoughtful about the user, and comfortable learning in public.

Today I work across LLM applications, retrieval, agents, and cloud delivery. I enjoy the gap between a promising prototype and a system people can depend on, and I’m looking for a team where I can keep growing while contributing from day one.

EXPERIENCE & FOUNDATIONNG / 2026
2026 — NOW

AI Solutions Engineer

Conversational AI & retail automation · Rasa project collaboration

2024 — 2025

AI Engineering · Ironhack

Intensive training in machine learning, NLP, LLM applications, and deployment

2013 — 2024

Operations & management

Team leadership and service operations in The Hague and London

04 / LET'S CONNECT

Let's build something
worth using.

Exploring AI engineering roles, thoughtful collaborations, and interesting problems. I’d be glad to hear what you’re building.