I am VP, Technology at Think Talent. I lead the development, DevOps and QA teams. I love building new things, and tech is a part of my life.

I have been building technology for leadership and talent assessment for more than 15 years. Today I run technology at Think Talent as VP. The development team lead, the DevOps manager and the QA team lead report to me.

I decide the architecture, set the direction for the teams and own what goes to production. I also stay hands-on. I build full stack solutions: the frontend, the backend, the data and the infrastructure they run on. In the last few years AI has become a big part of that work, and today it is at the centre of the products we build. I am actively involved in it every day, from running models on my own machine to fine-tuning them for a specific job.

I am not looking for a job. I made this page so that anyone who looks me up can see what I know and what I am working on.

Current role
VP, Technology at Think Talent
Teams that report to me
Development, DevOps, QA
Experience
15+ years
Industries I have worked with
Banking and insurance, energy, manufacturing, consumer brands

Development

The development team lead reports to me. I set the architecture and review the design decisions that matter.

DevOps and cloud

The DevOps manager reports to me. I have dealt with all kinds of AWS scenarios over the years, so I can guide the team from my own experience.

Quality

The QA team lead reports to me. I push for automation so that a release does not depend on manual testing.

Security

Platform security is my responsibility as well. Nothing goes live without a review.

These are the things I use in real projects. I have grouped them the way I think about them. As you scroll, the map behind the page turns to the group you are reading.

AI solutions

A big part of my work now. I take it from the first prompt to the evaluation that tells me if it really works.

  • LLM orchestration
  • Agents and tool use
  • RAG
  • Prompt engineering
  • LLM evaluation
  • MCP servers
  • Claude and OpenAI APIs
  • AI coding workflows
  • AI assessment pipelines

AI models and tools

I work with AI every day, hands-on. I run models locally with Ollama and LM Studio, fine-tune them with Unsloth, and use Claude, Codex, Grok and Google AI Studio. I pick whichever fits the job.

  • Claude
  • Codex
  • Grok
  • Google AI Studio
  • Ollama
  • LM Studio
  • Unsloth

Machine learning

I build and use custom models for different solutions. A ready-made API is not always the right answer.

  • Custom-built models
  • PyTorch
  • Hugging Face Transformers
  • scikit-learn
  • NumPy and pandas

Backend

Java and Spring Boot have been my base for many years. For AI work I mostly use Python and FastAPI. When the same code is needed in many places, I build it as a library.

  • Java
  • Spring Boot
  • Custom Java libraries
  • Python
  • FastAPI
  • Custom Python libraries
  • REST APIs
  • Data pipelines

Frontend

I build the screens as well. This site is made with Next.js.

  • React
  • Next.js
  • Vite
  • TypeScript
  • Custom npm libraries

Cloud

AWS is my main cloud and I have dealt with all kinds of AWS scenarios over the years. I also use Azure and Google Cloud for different use cases.

  • AWS
  • Azure
  • Google Cloud
  • EC2
  • S3
  • RDS
  • Lambda
  • CloudFront
  • Bedrock
  • IAM
  • VPC
  • CloudWatch

DevOps

My DevOps manager runs this day to day. I like releases to be boring. Automate it once and stop worrying about it.

  • Docker
  • Jenkins CI/CD
  • Git
  • Infrastructure as code
  • Monitoring

Cybersecurity

Our clients are large enterprises, so security checks are part of every release. I do the code reviews and testing myself as well.

  • Application security
  • Secure code review
  • OWASP Top 10
  • VAPT
  • Platform security

Test automation

My QA lead runs the team. If a test can be automated, we would rather not do it by hand.

  • Playwright
  • QA automation

AI in assessment

Rebuilding our core assessment products around what AI models can do today. Adding a chatbot on top of the old flow was never going to be enough.

AI for enterprise talent teams

Taking 15 years of assessment methods and turning them into solutions a large company can start using quickly.

A team that runs without me

Setting up onboarding, delivery and QA so the team can take a project from start to finish on its own.