Manfred Nesti

Manfred Nesti

Data & AI Engineer

I build LLM-powered systems and the data platforms behind them — from AI agents and semantic search to real-time streaming pipelines and high-performance scientific simulations.

Get in touch Download CV GitHub LinkedIn

About

I am a Mathematical Engineer with a master's in Computational Science and Computational Learning from Politecnico di Milano (110/110 cum laude). My work sits at the intersection of AI & Data Science, Data Engineering and Scientific Computing, with a strong focus on designing and deploying LLM-powered systems and scalable data platforms.

My experience spans production pipelines for AI agents, document extraction and semantic search, alongside big data, cloud data warehousing and real-time processing — from high-throughput Spark and Kafka streaming to cardiac-muscle modelling on HPC clusters.

Since 2018 I am a Co-Founder and Data Advisor at thefaculty, where I help shape data and AI strategy for product teams.

Read the full curriculum →

Skills

AI & LLM
  • LLM systems
  • AI agents
  • RAG
  • Semantic search
  • Document extraction
  • OpenAI
  • GPT-4
Programming
  • Java
  • Scala
  • Python
  • SQL
  • JavaScript
Data Engineering
  • BigQuery
  • Spark
  • Kafka
  • Airflow
  • Delta Lake
  • Databricks
  • MongoDB
ML & AI
  • scikit-learn
  • TensorFlow
  • Keras
  • Pandas
  • NumPy
  • OpenAI
Back-End
  • Spring Boot
  • FastAPI
  • Flask
Cloud
  • Google Cloud
  • Cloud Run
  • Pub/Sub
  • Looker Studio
  • AWS EMR
  • S3
  • Lambda
DevOps & CI/CD
  • Docker
  • Kubernetes
  • Helm
  • Cloud Build
  • Bamboo
Tools
  • Git
  • Jupyter
  • Postman
  • Linux / Bash
Languages
  • Italian: native
  • English: B2

Experience

  • Jan 2026 — present

    Data Engineer

    Brix

    Building modern data platforms with FastAPI services and cloud data engineering on AWS.

  • Oct 2022 — present

    Co-Founder & Data Advisor

    thefaculty

    Shaping data and AI strategy for product teams, after leading the data function as Head of Data.

  • Sep 2022 — Dec 2025

    Big Data Engineer

    Agile Lab

    Java/Spring Boot microservices and Scala/Spark streaming on AWS EMR, with high-throughput Spark and Kafka pipelines (1000+ msg/sec) for electric-grid monitoring.

See the full curriculum →

Selected projects

Data Engineering

Real-time ETL: MongoDB → BigQuery

Python multiprocessing pipeline with automatic schema detection from the MongoDB OpLog, containerised for deployment.

Scientific Computing

Oxygen exchange in cardiac muscle

Finite-element modelling in C++ with simulations run on an HPC cluster.

Machine Learning

Face-mask classification CNN

Transfer learning and ensemble methods, reaching 95% test accuracy (top 20% of the leaderboard).

See all projects →

Contact