TUM M.Sc. Informatics • Cloud, Data & AI Engineering
Carlos Mejia
Cloud & Data Engineer & Applied AI Researcher
Bridging rigorous academic AI research at Technical University of Munich with 9+ years of enterprise software and data platform architecture across AWS and GCP. Focused on production infrastructure-as-code, multi-environment data pipelines, MLOps, and agentic workflows.
- Munich, Germany
- carlos.mejia@tum.de
- GitHub
About
Carlos has more than nine years of experience in software and data development, combining consultancy, startups, and large companies across mobility, logistics, media, and healthcare. He has led teams of 2 to 3 people and is currently expanding his technical experience and knowledge with a master's degree in Informatics at TUM Munich, focused on cloud computing, machine learning, including deep learning and natural language processing, and software engineering.
He is equally comfortable in the fast-paced environment of a startup, where he has designed data architectures from scratch, and in the more structured environment of a large company, where he has built production infrastructure at scale. That combination allows him to bring strong engineering practices to small teams without slowing down the speed they need.
He is excited by complex technical and business challenges related to collecting, interpreting, analyzing, and modeling data, and increasingly with orchestrating AI agents in real engineering workflows. He also enjoys sharing his knowledge, as he has taught classes at both personal and university levels on topics such as machine learning, MLOps, data engineering, and data analysis.
Core Competencies & Architectural Pillars
Bridging enterprise-grade cloud and data platform engineering with rigorous academic AI research at TUM Munich.
Production Cloud Infrastructure & IaC
Architecting resilient multi-environment infrastructure on AWS and GCP with reproducible Terraform and AWS CDK, hardened IAM/KMS security policies, and zero-downtime deployment pipelines.
Enterprise Data Platforms & Streaming
Designing high-throughput batch and real-time streaming ETL architectures (EMR/Spark, Kafka, AWS Glue, BigQuery) processing hundreds of millions of records across hybrid cloud stacks.
Agentic AI & Knowledge Graphs
Engineering structured Knowledge Graph retrieval layers and orchestrating AI coding agents in real software delivery workflows with LangChain, Weaviate vector databases, and LLMs.
DevOps & GitOps Reliability
Establishing automated CI/CD deployment gates, local database migration test stacks in GitHub Actions, containerized Docker microservices, and Postgres RLS security architectures.
Applied AI Research (TUM Chair)
Designing and evaluating structured KG retrieval layers against benchmark architectures (RegulaRAG, LightRAG, HippoRAG 2) for regulatory test scenario generation from UN Regulation 152.
Technical Instruction & Mentorship
Teaching university master's courses at ITESM and industry workshops in MLOps, testing practices with Pytest, FastAPI microservices, and cloud data platform engineering.
Interactive Skill Matrix
Click any skill to highlight related career milestones, architecture projects, and research artifacts across the site.
☁️ Cloud & DevOps
📊 Data Engineering
🧠 AI & Software
Career & Research Timeline
Maintain AWS infrastructure as code with Terraform and AWS CDK across two production services; build batch data pipelines with EMR/Spark, AWS Glue, and Python; configure cross-service IAM roles and security hardening (KMS, Secrets Manager, VPC).
Sole full-stack developer and product owner for a community management platform with 60+ active users. Built frontend with React 19, TypeScript, Vite, and backend on Supabase (Postgres with RLS, serverless Deno Edge Functions, Auth, Storage) with AI-agent-orchestrated development.
Collaborated with CTO to implement scalable AWS data architecture (S3, Lambda, Redshift, Step Functions); developed ~10 ETL pipelines with Python connecting external APIs with up to 400% execution speedups.
Schema-Guided KG Construction and Retrieval for LLM-Based Automotive Test Scenario Generation from UN Regulation No. 152. Benchmarking flat vector retrieval, LightRAG, and HippoRAG 2 against 59 annotated test scenarios.
Designed data roadmap and observability infrastructure; built batch data pipelines with Airflow Google Composer, BigQuery, Docker, and Terraform.
Invited lecturer at the Master's in Applied Artificial Intelligence (MNA-V) at Tecnológico de Monterrey; taught courses in Python, Pytest, FastAPI, Docker, Terraform, and GitHub Actions applied to MLOps.
Developed streaming and batch pipelines for enterprise clients including NBCU and Dow Jones across GCP and AWS; built REST API for machine learning with FastAPI and Docker; taught Terraform and Kafka.
Consolidated MySQL, Postgres, and MongoDB into a Kafka cluster (500M+ records); built Apache Beam streaming pipelines on Dataflow and AWS S3 data lake with Glue, Athena, and QuickSight.
Productized automated GUI app saving 40+ hours/month using Python and Django; built document processing prototype using Deep Learning (ResNet-50) and OCR with 81% accuracy.
Featured Projects & Field Notes
In-depth technical write-ups, architectural trade-off evaluations, and applied research deliverables.
Salsuki: Append-Only Ledger & Postgres RLS Engine
Architecting a zero-loss credit economy (`SUM()` ledger at read time), atomic SQL `SECURITY DEFINER` RPCs, and local Supabase CI testing in GitHub Actions.
Schema-Guided KG Retrieval for Automotive Test Scenario Generation
Comparative evaluation of retrieval strategies (flat vector retrieval, LightRAG, HippoRAG 2) and automated schema-guided Knowledge Graph construction for UN Regulation No. 152 test scenarios.
LECture-bot: Academic RAG with LangChain & Weaviate
Building multi-modal lecture indexing and hybrid vector similarity retrieval to ground LLM student responses accurately on university course materials.
Degrees, Certifications & Honors
Academic degrees from top-tier institutions, specialized multi-cloud credentials, and academic recognitions.
Academic Degrees
Technical University of Munich (TUM)
Master of Science in Informatics • Oct 2023 – Expected Apr 2027
Coursework in Cloud Computing, Cloud Information Systems, Cloud-Based Data Processing, DevOps, Machine Learning, and Requirements Engineering. Thesis research at the Chair of Robotics, AI and Real-Time Systems.
Instituto Politécnico Nacional (UPIITA)
Bachelor of Computer System Engineering • Jan 2015 – Jul 2020
Rigorous engineering coursework in Artificial Intelligence, Software Engineering, Distributed Computing, Microcontrollers, and Databases. Graduated in top 5% of cohort.
Universidad de Caldas
Student Exchange in Computer System Engineering • Jan 2019 – Jul 2019
International student exchange program focused on Machine Learning and advanced software engineering coursework.
Cloud Architecture Experience & Academic Appointments
Multi-Cloud & Infrastructure as Code
AWS • Google Cloud • Microsoft Azure
Hands-on production and academic architecture experience across AWS (CDK, Terraform, S3, Lambda, Redshift, EMR), GCP (BigQuery, Composer, Functions), and Microsoft Azure (Azure Functions, Blob Storage, Redis Cache, LUIS).
University Lecturer Appointment
ITESM Master's in Applied AI • 2022 – 2023
Appointed lecturer teaching graduate courses in MLOps, automated testing with Pytest, containerized FastAPI microservices, and production CI/CD deployment pipelines.