About
I take AI from an idea to something that works. Ten-plus years building software that holds up in the real world.
AI is a confusing place right now, for everyone. The tooling evolves monthly. Yesterday's best practice is today's dead end. And the hard part was never the idea. It's the distance between a demo that dazzles and a system that still works on Monday morning, with real people and real data going through it. That distance is where I work.
What that takes is end-to-end ownership: the framing, the research, the architecture, the build, the launch, and the 3am phone call afterwards. Working out what is actually possible, what it genuinely costs, and what is hype. What comes out the other side is a system that runs.
In practice that means insights platforms built on high-volume data: the large-scale processing and analysis underneath that turns vast, messy, real-world data into something a business can act on, and the AI applications on top that people actually use: retrieval that stays grounded, agents that call tools and hold state, and the evaluation that shows whether any of it holds up with real users in front of it.
Underneath every one of those systems sits the machinery that decides whether it survives: distributed, event-driven architecture on AWS and Kubernetes, horizontally scalable, resilient, fed by ingestion pipelines carrying millions of records a day, where "mostly correct" means silently wrong. Production AI is a distributed systems problem long before it is a model problem.
I work remotely. I am active at conferences, where this field gets argued over years before it reaches a changelog. Staying on the bleeding edge is part of the job.
The road here was deliberate. Engineering in the Dutch startup space. Research and software engineering at a university, teaching undergraduate and Master's Computer Science classes, and publishing peer-reviewed research on large-scale data integration. Then adtech startups, and after them a global leader in adtech. Performance-critical systems where latency, scale and correctness were never negotiable, because in that industry being wrong is measured in money per second.
Behind it: an Engineer's Degree in Informatics Engineering, a Master's Degree in Computer Science, AWS Certified Solutions Architect – Associate, and three peer-reviewed IEEE publications. I have published in this field as well as built in it.
Resume / CV
Downloadable PDF coming soon
Experience
Lead AI Engineer
EXTE, global leader in adtech
2023 – Present
- Applied AI R&D: insights platforms and AI systems built on large-scale data processing and analysis.
- AI applications on top of that data layer: retrieval and grounding, agentic workflows that call tools and hold state, and the evaluation harnesses that establish whether they actually work.
- The distributed infrastructure underneath: event-driven, horizontally scalable services and ingestion pipelines carrying millions of records a day.
- End-to-end ownership: problem framing, research, architecture, implementation, deployment and ongoing operation.
- Working at the point where the field is still being figured out, and translating it into things that ship.
Lead Software Engineer
Noddus, acquired adtech startup
2019 – 2023
- Designed and built the software behind the company's core product: a programmatic-advertising integration system interfacing with multiple providers including DV360 and Facebook.
- Worked in tandem with the product team to deliver new features quickly and effectively, staying ahead of the market.
- Built internal tooling to bridge cross-team communication gaps and enable straightforward system monitoring.
- Fully responsible for my work end to end: first planning steps, build, production delivery, documentation and long-term support.
Software Engineer / Research Associate
Aristotle University of Thessaloniki, one of Greece's top universities
2017 – 2019
- Developed backend, mobile and analytics software in the big data sector for PTwist, a Horizon European open platform for plastic lifecycle awareness, monetisation and sustainable innovation.
- Social network integrations and mass data collection.
- Teaching Assistant on the university's undergraduate and Master's Computer Science programmes, delivering full class presentations on software and database technologies.
- Responsible for the lab's DevOps and infrastructure.
Software Engineer / Co-Founder
Reactive IoT
2018 – 2019
- Built a prototype to test in the Industry 4.0 sector.
- Over-the-air industrial production-line data collection using custom IoT modules and sensors.
- 24/7 live factory production-line monitoring from any user device.
- Production-line breakdown prediction, preventing halts caused by sudden equipment failure.
Backend Software Engineer
Lokalinc, Rockstart-accelerated startup, Netherlands
2015
- Replaced the platform's item search engine with a dedicated search backend.
- Built the shopping cart functionality and the PDF invoice generation system.
- Created unit and integration tests across the whole codebase while refactoring to reduce technical debt.
Education
MSc, Computer Science
Aristotle University of Thessaloniki, one of Greece's top universities
2016 – 2018
- Thesis: Data Integration of multiple Social Media platforms.
- Distributed databases, parallel workloads and large-scale processing.
- Graph databases and algorithms.
- Machine Learning.
Engineer's Degree, Informatics Engineering
International Hellenic University
2010 – 2015
- Thesis: Java code obfuscator.
- Core informatics and hardware architectures.
- Specialisation in software engineering and computer networking.
Certifications
AWS Certified Solutions Architect – Associate
Amazon Web Services · Credential ID a9bb2133619849f299bb9734d4d1e2e4 · Verify
Talks
coming soon
Publications
An Online Social Network Data Integration system based on reactive microservices
IEEE International Conference on Smart Computing (SMARTCOMP '18) · DOI
Learning Programming through Design
IEEE Global Engineering Education Conference (EDUCON '18) · DOI
Exploring Computational Thinking Skills in 3D Printing: A Data Analysis of an Online Makerspace
IEEE Global Engineering Education Conference (EDUCON '19) · DOI
In brief
Who is Alex Tsilingiris?
Alex Tsilingiris is a Lead AI Engineer with 10+ years shipping software into production. He builds applied AI on high-volume data and takes projects the whole distance, from the first idea to a system carrying real traffic.
What does Alex Tsilingiris do?
Builds insights platforms and AI systems on high-volume data: turning vast, messy, real-world data into answers a business can act on, the large-scale processing and analysis underneath, and the AI applications on top. End to end, every time: framing the problem, running the R&D, architecting, deploying, documenting and supporting it in production. What you end up with is a system that runs.
What is Alex Tsilingiris's engineering background?
AI engineering first: insights platforms at scale, retrieval and grounding, agentic systems that call tools and hold state, and the evaluation and observability that show how they behave in production. Underneath that, the distributed systems layer that makes it possible: horizontally scalable, event-driven architectures on AWS and Kubernetes, and ingestion pipelines carrying millions of records a day. Full ownership from problem framing through DevOps, delivery and support. He led the engineering behind a core product at a global leader in adtech.
What are Alex Tsilingiris's qualifications?
An Engineer's Degree in Informatics Engineering, an MSc in Computer Science, AWS Certified Solutions Architect – Associate, and three peer-reviewed IEEE publications. He has taught undergraduate and Master's Computer Science classes at university level, and has published in this field as well as built in it.
