CURRICULUM VITAE · APPLIED AI ENGINEER

Anthony Calek

An independent practice built on cross-domain experience: managing assets, understanding how businesses actually run, and engineering the software that connects them. The result is a measured approach to AI and process automation. Practical, not revolutionary.

Work-eligible: US · CH · CA

Contact ↓·Kaiserstuhl, Aargau CH·LinkedIn·GitHub·research.happycode.ch

THE FIELD

What I build, end to end.

These four domains are where my work converges. Across them, time-tested methods and a modern stack lift velocity without trading away quality. The repetitive parts are handled; the judgment, standards, and values become the guardrails that autonomous systems are taught to follow.

Every card is something I’ve shipped or run, grouped by where it lives and tagged by domain. The middle band is the cross-domain work: the LLM-native, automation, and operator layer where most of it actually sits.

FILTER BY DOMAIN

Select a domain to spotlight its cards; the rest recede to gray in place. The work is multi-tagged, so most cards answer to more than one. Click the active domain again to clear.

Data Science & Engineering
Fluent across cloud data stacks, and onto new ones fast through automated documentation and agent-assisted implementation.

Data Pipeline Engineering

Multi-source ingestion into one normalized store: APIs, databases, and unstructured documents parsed into structured data, refined through staging-to-gold layers.

Warehousing & Data Modeling

Relational and spatial data models in dimensional warehouses, with schemas built to evolve: forward-only migrations and version checks that keep code and data in lockstep.

Data Quality & Governance

Integrity audits that fail the build on broken data, quality and observability checks, and governance for residency and compliance, with human review where judgment matters.

Data Reliability & Reproducibility

Snapshot-before-change discipline, disaster-recovery drills that verify backups before they are trusted, and research that is reproducible by construction across self-managed environments.

Entity Resolution & Geo-Enrichment

Record matching and deduplication that reconcile messy real-world entities, with geocoding and spatial enrichment that put the data on the map.

Quantitative & Statistical Analysis

Out-of-sample backtesting with real multiple-testing rigor, academic valuation models, and statistical text analysis of filings, built to survive scrutiny rather than flatter a result.

Cross-Domain
Where the lanes meet: LLM-native building, agents, automation, and the operator systems that run it all.

Multi-Platform Expertise

Fluent operating across macOS, Linux, and Windows: self-hosted environments and tooling built to run wherever the work lives, not locked to one vendor's stack.

Document Intelligence & Data Analysis

Turning unstructured documents into structured data, and the analysis on top: extraction, parsing, and the statistics that make filings and records legible at scale.

Agentic Development

Building with agents the way the field now does: orchestration for bounded, verifiable workflows, with evaluations that keep them honest rather than impressive.

Agentic Project Management

The discipline of scoping, delegating, and guardrailing work, now extended to a non-human workforce: bounded autonomy, human-in-the-loop gates, and accountability that stays with the operator.

Prompt & Context Engineering

Designing the prompts and the context a model actually sees, with the judgment for what to give it and what to withhold, so the output stays reliable.

Spec-Driven Development

Specifying work as verifiable tasks before building, so agents and people execute against a clear contract instead of guesswork.

Knowledge Capture & Dissemination

Capturing expert judgment, standardizing it, and making it reusable, so knowledge compounds across a team instead of walking out the door.

Business & Financial Operations
Running and financing real operations: professional asset management, the automation that streamlines it, and disciplined work in the markets.

Real-Estate Asset Management

Professional asset management at portfolio scale: multi-family investing and underwriting, operations, and the finance and accounting that drive the returns.

Operations & Process Automation

Mapping how an operation actually runs and automating the parts that drag, from leasing and CRM to reporting and accounting, so the process outlasts the people who built it.

Leadership & Stakeholder Management

Managing teams and the hard conversations: tenants, investors, lenders, and partners, with the judgment to defend a position and the patience to resolve conflict.

Regulatory & Compliance Literacy

Working fluently inside Swiss and EU data rules (nLPD, revFADP, FINMA-aware) and the residency requirements that regulated work depends on.

Risk Management & Trade Planning

Swing and futures trading with capital preservation first: positions planned from macro signals, technicals, and the filings behind them.

Investment Research & Trading Tooling

Validated, automated investment research and the tools behind it: broker-statement analyzers, custom indicators, and ROI calculators that turn data into decisions.

Trade Analysis & Market Behavior

Reading performance patterns and institutional behavior, from liquidity and market-maker dynamics to the discipline that keeps decisions tied to evidence over narrative.

EXPERIENCE & CREDENTIALS

The conventional version.

Founder & Applied AI Engineer

happycode.ch, Kaiserstuhl, CH (with US partners) · 2022–present

Independent Trading Strategy & Analytics

happycode.ch · Sep 2024–present

Principal Asset Manager

Calek-PM, Chicago, IL · 2012–2021

EDUCATION

Business & Asset Management

Computer Science

LANGUAGES

EN · DE · CH-DE · SE

CERTIFICATIONS

Data Engineering

Project Management

CRM

GET IN TOUCH

A free first conversation. In your office. Often same day.

Most of my work starts with a short conversation. If you have a small technical problem you don’t know what to do with, or a larger problem you’re not sure how to scope, that conversation is the right next step. There’s no obligation and no pitch. I’ll tell you whether I’m the right fit, and if I’m not, I’ll usually know who is.

Or send a note

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