Solutions Architect · Amsterdam

Anastasia
Pachni Tsitiridou

Building agentic AI systems and cloud infrastructure that turns complexity into clarity — at the intersection of technology and real-world impact.

Anastasia Pachni Tsitiridou standing among sage green shrubs by the sea

Curiosity as a compass

My journey began with an endless curiosity for how things work — from computers and film cameras to ATM machines, always drawn to unravelling the underlying logic of technology. I thrive on creating robust solutions and tackling technical challenges, constantly seeking to learn new domains and master unfamiliar territory.

Originally from Greece, I embraced my love for real-world applications by co-founding a startup, an experience that fuelled my passion not just for technology but for the art of building businesses. To deepen my understanding, I pursued a master's degree in finance alongside computer engineering — an education that equipped me to bridge the worlds of technology and entrepreneurship with clarity and purpose.

Today, I call Amsterdam home and work at KPN, where I design agentic AI systems and cloud infrastructure for telecommunications — exploring the boundless possibilities that modern AI and cloud unlock for mission-critical operations. I devote my energy to tackling impactful, complex problems, collaborating and learning from others; each experience helping me uncover the influences and ambitions that define my journey.


Career

My career started where it felt most natural — building real things. Co-founding a startup while still a student gave me a taste of what it means to own a problem end-to-end, and that instinct has shaped everything since. From there I joined AWS as an Associate Solutions Architect through their graduate program, and over five years earned two promotions to L6 — working across cloud modernisation, ML, and generative AI, speaking at re:Invent and re:MARS, and writing for the AWS ML Blog. I left not because I'd run out of road, but because I wanted to be closer to the product — architecting systems that matter in production. That's what brought me to KPN.

KPN

Amsterdam · Feb 2026 – Present

Current

Solutions Architect — Agentic AI

Designing scalable agentic AI architectures for autonomous network operations. Translating business goals into implementable blueprints, driving governance, and coaching teams on responsible AI delivery.

Amazon Web Services (AWS)

Amsterdam · Sep 2020 – Jan 2026 · 5 yrs 5 mos

Senior Solutions Architect Apr 2025 – Jan 2026
Solutions Architect Jul 2022 – Apr 2025
Associate Solutions Architect Sep 2020 – Jul 2022

Over five years, grew from graduate hire to L6 — advising customers across cloud modernisation, ML, and generative AI. Featured speaker at re:Invent 2024 and re:MARS 2022. AWS ML Blog contributor reaching 15K+ readers.

Early-stage startup

Greece · Feb 2017 – Nov 2019

Co-founder & Software Engineer

Built and shipped as a co-founder while still completing my engineering degree — Python, data science, and ML prototypes. The experience of building something from nothing set the tone for everything that followed.


Projects & Initiatives

01

AWS · Machine Learning

Fine-tuning GPT-J with SageMaker Model Parallelism

Co-authored AWS blog post and implementation guide for training a 6-billion-parameter GPT-J model using Amazon SageMaker's distributed model parallel library. Covers tensor parallelism, pipeline parallelism, and FP16 training to reduce cost and time at scale.

  • Amazon SageMaker
  • Hugging Face
  • GPT-J
  • Tensor Parallelism
  • PyTorch
Read on AWS Blog ↗
2023
02

Open Source · Python

Dynamic CVaR ETF Allocation

Hybrid ETF portfolio optimisation framework combining CVaR constraints, DCC-GARCH modelling, and Ledoit-Wolf shrinkage for enhanced tail risk management. Integrates VixFix-based regime detection, Monte Carlo scenario generation, and bootstrap backtesting to deliver superior drawdown protection during market stress events.

  • Python
  • CVaR Optimisation
  • DCC-GARCH
  • Ledoit-Wolf
  • Monte Carlo
View on GitHub ↗
2025
03

Open Source · AWS

Rekognition Video People Blurring (CDK)

Serverless pipeline that uses AWS Step Functions to orchestrate Lambda functions calling Amazon Rekognition for face detection, then applies OpenCV to blur detected faces frame-by-frame in video — enabling privacy enforcement at scale. Deployed via AWS CDK with containerised Lambda runtimes.

  • AWS Step Functions
  • Amazon Rekognition
  • AWS Lambda
  • OpenCV
  • AWS CDK
View on GitHub ↗
2021

Skills & Domains

Architecture & Cloud

  • Microsoft Azure (Container Apps, VPC, networking)
  • AWS cloud services
  • Multi-tenant system design
  • Microservices & container orchestration
  • Infrastructure-as-Code

Agentic AI

  • Multi-agent orchestration (LangGraph)
  • RAG & GraphRAG pipelines
  • Vector databases & semantic search
  • Prompt engineering & AI governance
  • LLM evaluation & deployment

Delivery & DevOps

  • CI/CD pipeline design & governance
  • Kafka event streaming
  • Python & IaC tooling
  • Git-based workflows
  • Deployment strategies & rollout

Finance & Quant

  • Portfolio optimisation & risk management
  • CVaR, DCC-GARCH & covariance modelling
  • Monte Carlo & backtesting
  • MSc International Finance
  • Startup co-founder

Beyond the terminal

  • WSET Level 2 — working toward Level 3
  • Baking & specialty coffee
  • Photography (Fujifilm)
  • Live music & concerts
  • Dutch language learner (A2)

On the nightstand

  • Human Acts — Han Kang
  • The Big Short — Michael Lewis
  • Equality: What It Means and Why It Matters — Thomas Piketty

Let's connect

I'm always open to conversations about agentic AI, cloud architecture, or interesting problems at the edge of technology and business. Reach out through any of the channels below.

Based in Amsterdam

Open to conversations

Whether you're working on a complex AI architecture challenge, curious about telco domain applications of agentic systems, or simply want to exchange ideas — I'd love to hear from you.

Particularly interested in connecting with engineers, architects, and researchers pushing the boundaries of what AI systems can do in production.

Say hello