Hi, I'm Dino
AI Developer
I build agentic AI systems at BlueCallom in Zurich.
My story so far
I moved to Switzerland in 2018 with no connections in tech and no degree. I spent six years in landscaping - mowing lawns, cutting trees and eventually running a team of 8 across 170+ properties. The entire time I was teaching myself to code at evenings.
In early 2025 I joined BlueCallom AG as an AI developer, where I now build agentic AI systems that automate real business workflows from sales pipelines to compliance processes.
I'm also finishing a BSc in Applied Artificial Intelligence at IU International University. Not because I need the paper but because I genuinely want to understand the math and theory behind what I use every day.
AI Developer
BlueCallom AG, Zurich
BSc Applied Artificial Intelligence
IU International University
Switzerland
Menzingen, ZG
My path
Feb 2025 — Present · Zurich, Switzerland
AI Developer
BlueCallom AG- Built end-to-end agentic AI solutions automating business processes across Sales, Product Launching, Innovation, Compliance and custom agentic AI solutions.
- Developing and shipping new enterprise AI platform features using Python, Django and OpenAI API.
- Wrote requirement documents, defined implementation approach, and tested features across the platform
Jan 2020 — Jan 2025 · Baar, ZG, Switzerland
Gardener → Head of Garden Maintenance
R. Zurcher Hauswart-Service GmbH- Started as a gardener, promoted to department head within a year
- Managed a team of 5+ across 170+ property contracts
Jun 2018 — Dec 2019 · Zug, Switzerland
Landscaper
Gartenbau A. Hurlimann GmbH
- Commercial and residential landscaping
Feb 2015 — Feb 2018 · Zagreb, Croatia
Warehouse Worker → Warehouse Manager
SALESIANER Gruppe- Ran daily warehouse operations and inventory management
What I've built
Multi-Tenant RAG Pipeline System
Provider-agnostic agentic RAG framework. An LLM agent receives a query, builds an execution plan, then loops through tools — semantic search, SQL queries, dependency checks — until it assembles a complete answer. Multi-tenant by design.
Phi-3 Cloud Deployment
Infrastructure-as-Code project deploying Microsoft Phi-3 Mini (3.8B, 4-bit AWQ) as a streaming inference API on AWS. Six Terraform modules cover networking, ECS on GPU instances with auto-scaling to zero, ALB with WAF rate limiting, CloudFront + S3 frontend, and CloudWatch dashboards with alerting.
ArXiv AI Research Trends
Unsupervised learning analysis of 181k+ AI papers from ArXiv (2024-2026). Tested 9 embedding × clustering combinations, validated clusters against ArXiv categories using ARI and NMI, and identified growth trends via linear regression. Cluster labels generated automatically using Claude API.
Say hello
Feel free to reach out if you have any questions or would like to get in touch.
dino.smuc@gmail.com
Location
Menzingen, Switzerland