München, 30.09.2026

Profile Vladislav Vorobev

Foto VAVPC
80469 München
☎ +49 1772597575
✉ j@vavpc.de

Software & DevOps Engineer — AI | LLM | Agents Infrastructure | Kubernetes | Hardware

Interests and Objective

Delivers across the stack — backend, infra, hardware, ML/LLM workloads — with AI agents and AI pipelines as everyday tooling for codegen, refactors, test scaffolding, and code review; agent-driven development as the default workflow. Foundation in Python, Rust, TypeScript, distributed systems, and Kubernetes, including bare-metal, hardware-controlled clusters. Ships production LLM agents (RAG, tool-using, MCP) and LLM/RAG evaluation pipelines. Code costs nothing, no human review: AI-driven SDD/TDD/BDD — agents write the spec, the tests and the code.

Recent projects / employment

Project name or position

Period

Company

Google Distributed Cloud air-gapped (GDCag) – DevOps & Hardware

08/2025 – present

Google

AI-Driven E-Commerce Platform – Agents, RAG and ERP Integration

12/2024 – 08/2025

DesignWeltDeko

SAP Compliance Audit Framework

06/2024 – 12/2024

SAP

Senior Python Developer – Battery Testing & Cloud Migration (Automotive)

01/2023 – 05/2024

Mercedes-Benz

Design and Development of a Distributed Self-Audit Framework

05/2019 – 12/2022

SAP

Big Data Engineer – Java, Python & AWS

05/2018 – 12/2021

Skoobe

Big Data Processing for Automotive Safety Systems – Emergency Brake & Lane Assist

01/2018 – 05/2020

MAN Truck & Bus

IoT Cloud Platform – Cross-Platform Connectors & DevOps

01/2016 – 12/2018

Mozaiq

ERP & Analytics Platform – Lead Generation and Online Marketing

01/2016 – 12/2016

FitnessClubs AV

Global E-Commerce Platform – Localisation & Warehouse Management

01/2013 – 12/2015

[Confidential]

Before 2015 – Leadership Roles and Early Projects

2005 – 2014

various

pois.world — Open map & virtual-parcel platform

2025 – present

Personal project

For full descriptions, see the Recent projects / employment details section below.

Education

map to buried treasure
map to buried treasure

Cologne University of Applied Sciences (TH Köln, formerly FH Köln)

2002 – 2009

Faculty: Informationstechnik in der Nachrichtentechnik

  • Title: Dipl.-Ing. Elektrotechnik

  • Diploma thesis topic: Developed a neural network-based system for image region detection and character classification, implementing Hu Moments for translation, rotation, and scale invariance in C programming.

Lomonosov University 2005 – 2006

  • Faculty of Computational Mathematics and Cybernetics (student exchange program)

Seminars 2005 – 2008

  • Negotiation skills, Living and Working in a Globally Oriented World, International Project Management across Borders, English (WSI), and others

map to buried treasure
map to buried treasure

Telefonbau Nagel GmbH, Cologne / Georg-Simon-Ohm-Berufskolleg 1999–2002

  • Double qualification as IT-Systemelektroniker at Telefonbau Nagel GmbH (now Simply Communicate).

Skills

AI / Agents

  • LLMs: OpenAI, Claude (Anthropic), Hugging Face / open-weights

  • Calling patterns: function / tool calling, structured outputs (Pydantic, JSON Schema), streaming, vision, prompt caching, batching

  • Agent frameworks: LangChain, LangGraph, PydanticAI, CrewAI, OpenHands, plain-Python tool-using agents

  • Agent patterns: ReAct, planner-executor, multi-step orchestration, sub-agents, autonomous + human-in-the-loop, escalation rules

  • MCP (Model Context Protocol): production MCP servers (pois-mcp), MCP clients, tool / resource / prompt exposure to AI assistants

  • RAG stack: FAISS, pgvector, Weaviate; OpenAI and sentence-transformers embeddings

  • Retrieval: hybrid search (BM25 + dense), reranking, chunking strategies, query rewriting, citation grounding

  • Knowledge synthesis: spec / feature registries, internal docs, code search, chat history, ticket / PR history fused into agent context

  • Evaluation: golden datasets, hallucination detection, prompt regression, automated graders, LLM-as-judge with calibration, agent-behaviour validation; eval in CI

  • Prompt engineering: system-prompt design, few-shot, schema-driven output, guardrails, jailbreak resistance, persona / role design

  • Agent ops: cost / latency budgeting, retries, fallbacks, caching, observability (traces, token spend, eval drift)

  • Safety & compliance: PII redaction, content filtering, audit trails, deterministic mode for regulated paths

Agent-Driven Development

The way I build, not just what I build. Humans set direction; agents synthesise knowledge across the codebase, specs, docs, and PR history; humans review.

  • Workflow: Spec-Driven Development — Concept → Plan → Spec → Code → Feature discipline; spec / plan / feature registry the agents read from and write back to, referenced in code and PRs.

  • Project rails: CLAUDE.md and AGENTS.md define design principles, commit conventions, and no-go zones for autonomous edits.

  • Knowledge sources for the agent: code, spec/feature registry, ADRs, runbooks, prior PR diffs, eval logs — all reachable through tools or RAG.

  • Practical use: codegen, refactoring, test scaffolding, code review, architecture sanity checks, runbook authoring, IaC and tooling work, migration drafting.

  • Quality gates: typecheck, tests, LLM evals, security review — every PR; agents must produce green CI before a human approves.

  • Outcome on real projects: pois.world shipped solo (nine microservices, Rust core, four clients); vav-v2 (German tax / EÜR accounting) built the same way with strict Decimal correctness and tracked-table reinit pattern.

Software Development

  • Programming Languages: Python, Go, Groovy / JVM, Java, JavaScript, TypeScript, PHP, C / C++, Rust (learning)

  • Frameworks & Libraries (Backend & Data): FastAPI, Pydantic, FastStream, Pyramid, aiohttp/asyncio, Vert.x; prior production: Django, Flask, Tornado, Grails, Rails; Zope/Plone (legacy CMS)

  • Frontend Development: SvelteKit / Svelte, React, AngularJS, Bootstrap, Tailwind, HTML5/CSS3, Responsive Layouts, Liquid (Shopify Templates), MapLibre GL JS, CesiumJS

  • Architectural Concepts: Satellite (stable core + specialised satellites), Microservices, Event-Driven, CQRS, Client-Server, Service-Oriented, Data Mesh

  • Methodology & Practices: SDD, TDD, BDD, DDD, Clean Code, SOLID, schema validation (JSON Schema), code review, agent-driven dev

  • Databases: PostgreSQL/PostGIS, ClickHouse, MySQL/MariaDB, MongoDB, Cassandra, ScyllaDB, ZODB, Neo4j; ORM: SQLAlchemy async, GeoAlchemy2, Hibernate, GORM

  • Big Data & ETL: Apache Spark (PySpark), Airflow, AWS Glue, Databricks

  • Messaging & Streaming: Apache Kafka (event streaming, distributed log, ETL pipelines), RabbitMQ (message broker, task queues), Celery (distributed tasks), Hazelcast (in-memory grid, pub/sub), Redis (pub/sub, Streams, caching)

  • Protocols & Formats: JSON, YAML, XML, CSV, Excel, Markdown, Protobuf, Parquet, Arrow, GraphQL, REST, gRPC, WebSocket

  • Editors & Terminal: Vim / Neovim (with AI integrations), VS Code, PyCharm / IntelliJ IDEA, Cursor, Zed; tmux, Linux shell; kubectl, helm, k9s, lazygit; ripgrep, fd, fzf, jq

  • Networking: TCP/IP, HTTP/HTTPS; Kubernetes networking (Calico, Cilium / eBPF CNI); WireGuard; NAT

  • Hardware & Datacenter Gear: bare-metal servers (HPE, Dell); enterprise switching / routing (Cisco, Juniper, Arista); firewalls (Palo Alto, Fortinet); F5 load balancers; leaf-spine fabrics; out-of-band management (iLO, iDRAC, IPMI, Redfish)

Testing & QA

  • Unit, Integration, Functional, End-to-End, and Regression Testing

  • pytest, unittest, JUnit, Spock, Behave, Robot Framework

  • Mocking, Test Automation, Continuous Testing

  • LLM / RAG evaluation, agent behaviour validation, golden datasets, hallucination detection (covered in detail above under AI / Agents)

  • OpenTelemetry tracing for observability-driven testing (incl. OpenTracing, OpenCensus, Jaeger)

System Administration, Cloud & DevOps

  • Operating Systems: Linux (Debian, Ubuntu, Alpine, Arch, openSUSE), macOS, Windows

  • Containers & Orchestration: Docker, LXC, Kubernetes (MetalLB, Ingress-Nginx, Rook-Ceph), cgroups

  • Virtualisation: KVM, QEMU, libvirt

  • Cloud Providers: AWS (S3, RDS, Glue, Athena), GCP, Azure, Hetzner Cloud, eXtollo

  • CI/CD & IaC: Jenkins, GitHub Actions, GitLab, Concourse, Terraform, Nomad, Packer, Consul, Vault, Gradle, setuptools, pip, Buildout

  • Version Control: Git, Mercurial (hg), SVN

  • Monitoring & Metrics: Prometheus, Alertmanager, Grafana, Loki, Tempo, Grafana Alloy, OpenTelemetry, Beyla, Zipkin, Sentry

  • Networking & Security: Bonding, BGP, DNS, SSL/TLS, VPNs, IPsec, iptables/nftables, Wireshark, Nebula, OpenSSL, GnuPG, Let’s Encrypt

  • Web & Infrastructure: Nginx, Apache, HAProxy, Traefik, Varnish, Memcached, Samba

  • Mail & Messaging: Exim, Postfix, SpamAssassin, Dovecot, Courier, Bots, Matrix

  • Authentication & Directory Services: LDAP & OpenLDAP, Active Directory Integration, Single Sign-On (SSO), OAuth2

Domain Knowledge & Advanced Practices

  • E-Commerce & ERP: Development of custom ERP & E-Commerce platforms from scratch; ERP system integration (250+ employees); Integration with Shopify (APIs, Liquid templates), PayPal, Stripe, custom providers; SEO & Microdata (schema.org), Retargeting & Remarketing (AdTech, SSP, DSP)

  • APIs & SaaS: Google APIs (Analytics, Merchant, Ads, Identity), OpenAI/Claude APIs, Etsy/Amazon/eBay APIs, Meta/X/LinkedIn APIs, Telegram API, Wikimedia API

  • Collaboration Tools: Jira, Confluence, Bitbucket, GitHub, Redmine

  • Code Quality & Tooling: PEP8, Ruff, Black, Pylint, Mypy, SonarQube, CodeQL, Clang-Tidy, Checkstyle, SpotBugs

  • Modeling & Architecture: UML, Event Bus, Message Queues

  • Automation & Custom Tooling: Workflow automation for ETL, CI/CD, and infrastructure processes; development of custom scripts and utilities

  • Data Collection: Large-scale web crawling and scraping with Python (Scrapy, BeautifulSoup, async pipelines)

Non-IT Skills

  • Agile Leadership: Experienced in leading international IT teams (up to 15 members, including remote teams) within Agile frameworks (Scrum, SAFe)

  • Team & Project Management: Proven expertise in project organisation, staffing, time management, and cross-site coordination

  • Product Thinking & Design: Understands the product behind the code — user needs, business model, market fit; shapes concepts and roadmaps, contributes and challenges ideas, prioritises by value; took own products from idea to production (pois.world, e-commerce and ERP platforms built from scratch)

  • Ownership & Initiative: Drives topics end-to-end without waiting for tickets; proposes improvements to product, process, and architecture; comfortable with ambiguity and greenfield work

  • Stakeholder Communication: Strong focus on customer satisfaction, safety, and responsible decision-making; experienced in aligning technical goals with business needs

Recent projects / employment details

Google Distributed Cloud air-gapped (GDCag) – DevOps & Hardware

08/2025 – present, Munich (consulting)

Company: Google – Role: DevOps Engineer – Type: Consulting Project

  • DevOps for GDCag — isolated, on-premises Kubernetes for sovereign and regulated workloads

  • Deployment of GDC air-gapped on customer hardware: rack-and-stack, bring-up, network and storage integration, handover

  • Hardware controlled by Kubernetes: HPE and Dell bare-metal servers, fleet lifecycle and node operations driven from the cluster control plane

  • Networking: Cisco Nexus leaf-spine fabric, BGP, VLAN / VXLAN, Palo Alto firewalls; storage: NetApp ONTAP; GPU nodes (NVIDIA)

  • Custom controllers, CRDs, and operators in Go for hardware operations and lifecycle automation

  • Kubernetes cluster operations, upgrades, and observability: Prometheus, Alertmanager, Grafana, Loki, Tempo, Grafana Alloy (OpenTelemetry)

  • Platform services inside the air-gapped cluster: Keycloak (SSO, OIDC), GitLab (repos, CI/CD, runners)

Tech Stack

  • Languages: Go (CRDs, controllers, operators), Python

  • Infrastructure: Kubernetes, Linux, macOS, Windows, HPE / Dell bare metal, NVIDIA GPU, GCP; out-of-band: iLO, iDRAC, IPMI, Redfish

  • Networking & Storage: Cisco Nexus, leaf-spine, BGP, VLAN / VXLAN, Palo Alto, NetApp ONTAP

  • Automation & Ops: IaC, lifecycle automation

  • Observability: Prometheus, Alertmanager, Grafana, Loki, Tempo, Grafana Alloy, OpenTelemetry

  • Platform Services: Keycloak, GitLab (CI/CD)

AI-Driven E-Commerce Platform – Agents, RAG and ERP Integration

E-Commerce Platform Screenshot

12/2024 – 08/2025, Munich (consulting)

Company: DesignWeltDeko – Role: AI Engineer / Full Stack Developer & DevOps Engineer – Type: Consulting Project

  • Designed and shipped customer-facing and internal AI agents — Product Chat (RAG over catalogue), Scene Generation, Text Generation, Image Classification — on OpenAI, Claude (Anthropic), LangChain, PydanticAI, FAISS

  • Worked agent-driven end-to-end (Claude Code, Cursor, Zed) for codegen, refactors, test scaffolding, code review

  • Built LLM and RAG evaluation pipeline — golden datasets, hallucination checks, prompt regression — to keep agents reliable in production

  • Connected a custom ERP (without an existing connector) to the Shopify API via an event-driven sync; products, prices, AI-classified images flow in real time

  • Shipped a Progressive Web App (JavaScript with React and Svelte) and Liquid storefront customisations; integrated marketplaces (eBay, Etsy, Amazon)

  • Designed and operated Kubernetes clusters (Calico, MetalLB, Ingress-Nginx, Rook-Ceph, PostgreSQL) on Hetzner Cloud and on-premises to host platform, vector store, and ERP

  • Stood up observability and ETL with Prometheus, Grafana, Loki, Tempo, OpenTelemetry, Beyla, Kafka, Airflow

  • Coached the team on LLM agents, prompt engineering, and AI-assisted workflows

Tech Stack

  • AI / Agents: OpenAI, Claude (Anthropic), LangChain, PydanticAI, RAG, FAISS, custom tool-using agents, LLM evals

  • AI-Assisted Dev: Claude Code, Cursor, Zed, Neovim

  • Languages & Tools: Python, JavaScript, SQL, Pandas, FastAPI, FastStream, Pydantic

  • Frontend: React, Svelte, Liquid (Shopify), HTML, CSS

  • APIs: Shopify, OpenAI, Etsy, Amazon, eBay; Google APIs (Analytics, Merchant, Ads, Identity)

  • DevOps & Infrastructure: Linux (Debian, Alpine), Docker, Kubernetes (Calico, MetalLB, Ingress-Nginx), Rook-Ceph, Gitea, Hetzner Cloud ↔ On-Premises, Networking, VPN

  • Monitoring, Metrics, Tracing, CI/CD & ETL: Prometheus, Grafana, Loki, Tempo, OpenTelemetry, Beyla, Kafka, Airflow (DAGs), Gitea Actions

  • Testing & Automation: pytest, Behave

  • Protocols & Formats: JSON, YAML, XML, CSV, Excel, HTML, Markdown, Protobuf, Parquet, Arrow, GraphQL, REST, WebSocket

SAP Compliance Audit Framework

SAP Automated Audit Framework

06/2024 – 12/2024, Walldorf

Company: SAP SE – Role: Software Engineer – Type: Consulting Project

  • Contributed to feature development for compliance and auditing software

  • Improved code quality through systematic refactoring of the Python codebase

  • Upgraded core framework and libraries (Python, Pyramid, supporting dependencies)

  • Collaborated with SAP teams to ensure maintainability and forward compatibility; Data Mesh patterns

  • Project follow-up and continuation of earlier work (see Design and Development of a Distributed Self-Audit Framework, 05/2019 – 12/2022, Walldorf)

Tech Stack

  • Languages & Frameworks: Python, FastAPI, Pyramid, SQL

  • Databases: PostgreSQL, SQLite

  • Cloud & Infrastructure: Linux, Docker, Kubernetes, Google Cloud Platform (GCP)

  • APIs & Security: REST API, OAuth, Single Sign-On (SSO)

  • Testing & CI/CD: pytest, GitHub Actions

Senior Python Developer – Battery Testing & Cloud Migration (Automotive)

Mercedes-Benz Automotive Software Project

01/2023 – 05/2024, Stuttgart

Company: Mercedes-Benz AG – Role: Senior Python Developer – Type: Permanent Position

  • Battery test data analysis optimised through microservices-based applications; end-to-end ownership from design and development to testing, deployment and operations

  • Cloud migration executed for battery testing applications and workloads to eXtollo / MIC – Azure Cloud (Container Apps, Databricks, VMs, Blob Storage, SQL, Cosmos DB, Spark); production go-live, Dev / Test / Prod environments, IaC (Terraform)

  • Data processing pipelines improved for automotive test data using Python, Pandas, Apache Arrow, and Delta Lake: time-series processing (resampling, windowing, aggregations, outlier handling), Delta Tables in production

  • REST APIs (FastAPI) developed and integrated for data access and service communication; pytest unit / integration tests, retry logic, structured logging, monitoring / alerting, stabilisation after go-live

  • Test and analysis results visualised via frontend components built with Svelte

  • Compliance, safety, and performance standards ensured in collaboration with cross-functional teams

Tech Stack

  • Languages & Frameworks: Python, FastAPI, Pydantic, multiprocessing, Pandas, Arrow, Svelte

  • APIs: REST APIs, Azure APIs (Identity)

  • Databases & Storage: MongoDB, SQL, Cosmos DB, Parquet, CSV, Delta Lake, MDF4 (battery test data format)

  • Cloud & Infrastructure: Azure (Container Apps, Databricks, Blob Storage, VMs, SQL, Spark), Docker, Linux, Windows

  • DevOps & CI/CD: Azure DevOps, Terraform, pytest

Design and Development of a Distributed Self-Audit Framework

SAP Self-Audit Framework

05/2019 – 12/2022, Walldorf

Company: SAP SE – Role: Lead Developer – Type: Consulting Project

  • Distributed microservices-based system designed and developed for automated corporate audit processes

  • Lightweight components implemented to run independently on client systems, collecting and evaluating audit-relevant data states

  • Alerting system built to notify customers of audit issues, with centralised servers generating reports and visualisations for external auditors

  • Resilience achieved through components able to handle high loads and network disruptions (offline operation without data loss)

  • Storage and data management improved with MinIO and cloud storage solutions (AWS, GCP); Data Mesh patterns

  • PostgreSQL database designed and administered, including performance tuning, backup strategies, data archiving, and monitoring

Tech Stack

  • Languages & Frameworks: Python, FastAPI, Pyramid, Pydantic, asyncio, aiohttp, multiprocessing, threading, pytest

  • APIs & Protocols: REST API, OpenAPI, HTTP, TCP, WebSocket, SSL

  • Databases & Storage: PostgreSQL, SQLite, MinIO, Cloud Storage (AWS, GCP)

  • Infrastructure & Messaging: Docker, Linux, Kubernetes, Kafka

Big Data Engineer – Java, Python & AWS

Skoobe Backend Development
Tolino Alliance

05/2018 – 12/2021, Munich

Company: Skoobe GmbH (Munich, member of the Tolino Alliance) – Role: Big Data Engineer (Python/Java) – Type: Consulting Project

  • Migration of microservices from Python 2.7 to Python 3, and from Java to Python

  • Development of asynchronous microservices in Java, Groovy, and Python

  • REST API and GraphQL server development

  • Migration of monolithic applications to microservices, including DevOps support

  • Migration of finance reporting system from Python 2 to Python 3 and to AWS Cloud

  • Documentation created and maintained for new and migrated services

Tech Stack

  • Languages & Frameworks: Python, Java, Groovy, FastAPI, Django, Tornado, asyncio, Pydantic, SQLAlchemy, Hibernate (Java ORM), lxml, JSON

  • APIs & Protocols: REST API, GraphQL, RPC, OpenAPI, Service Discovery

  • Databases & Storage: MySQL, NoSQL, SQL

  • Cloud & Infrastructure: AWS, Docker, LXC, Nomad, Consul, Packer, Ubuntu, Alpine, Nginx

  • Monitoring & Logging: Prometheus, Grafana, Elasticsearch, Logstash

  • CI/CD & Automation: Jenkins

Big Data Processing for Automotive Safety Systems – Emergency Brake & Lane Assist

MAN Truck & Bus Big Data Project

01/2018 – 05/2020, Munich

Company: MAN Truck & Bus AG – Role: Backend Developer (Data Processing) – Type: Consulting Project

  • Developed Spark-based solutions to process CAN-Bus data (BLF, DBC, MDF4.x) from Emergency Brake Assist and Lane Assist systems for graphical analysis

  • Designed and implemented distributed Spark jobs to parse, serialise, and classify terabytes of raw sensor data

  • Developed large-scale PySpark pipelines based on engineering requirements for preprocessing, aggregation, and transformation of automotive safety data

  • Implemented alerting and trigger mechanisms based on Spark-processed real-time and historical driving data

Tech Stack

  • Big Data & Processing: Apache Spark (PySpark), Hadoop (HDFS), AWS Glue Jobs, Athena, Impala, Hive

  • Databases & Storage: AWS S3, Parquet, MDF4, BLF, DBC (CAN-Bus formats)

  • Infrastructure & Cloud: AWS, Linux, Docker

  • Testing & Automation: pytest

IoT Cloud Platform – Cross-Platform Connectors & DevOps

Mozaiq IoT Cloud Project

01/2016 – 12/2018, Munich

Company: Mozaiq Operations GmbH (ABB, Bosch, Cisco joint venture) – Role: IoT Developer & DevOps Engineer – Type: Consulting Project

  • IoT platform developed to simplify cross-platform integration of consumer devices and services

  • Cloud connectors designed and implemented for manufacturers including Bosch/Siemens (BSH), Osram, Philips, Netatmo, and Regardia

  • Asynchronous, microservices-oriented architecture built with Vert.x and Grails, supporting horizontal scalability and high availability

  • Platform deployed on Kubernetes (GCP) with Docker, CI/CD pipelines in Concourse and Jenkins

  • Data security requirements implemented to meet enterprise-grade standards

  • Interoperability ensured across heterogeneous devices and vendor clouds via the Mozaiq cloud marketplace

  • Infrastructure as Code practices established for scalable deployments

  • Development performed in a Scrum team with Java, Groovy, and Python, including automated tests with Spock and pytest

Tech Stack

  • Languages & Frameworks: Vert.x, Grails, Groovy, Java, Python, Node.js, React, Gradle, GORM

  • Databases & Storage: MongoDB Cluster (replication + sharding), Hazelcast

  • Messaging & APIs: REST API, RabbitMQ

  • Infrastructure & Cloud: Docker, Kubernetes, GCP, Nginx, Docker Compose

  • CI/CD & Automation: Concourse CI, Jenkins

  • Testing: Spock, pytest

ERP & Analytics Platform – Lead Generation and Online Marketing

FitnessClubs AV ERP Project

01/2016 – 12/2016, Cologne

Company: FitnessClubs AV – Role: Software Developer & Architect (Full Stack) – Type: Consulting Project

  • ERP and analytics platform prototyped and developed for lead collection, processing, and statistical reporting

  • Responsive UI implemented with Bootstrap for customers and company managers

  • Existing PHP/Apache-based system migrated to a modern Python stack with data migration to a redesigned database model

  • System architecture and technical design specified, including ORM-based database modeling

  • Business logic and partner API integrations (REST) developed for multiple external providers

  • High-availability cluster and hosting solution designed and deployed on Debian/Linux with Docker and Nginx

  • Coordination of internal and external staff (IT, UX) throughout project phases

Tech Stack

  • Languages & Frameworks: Python (Python, Pyramid), JavaScript, React, jQuery, SQL

  • Frontend: HTML, CSS, Bootstrap

  • Databases & Storage: MySQL, Redis

  • APIs & Integration: REST APIs, Partner System Integrations

  • Infrastructure & Cloud: Debian GNU/Linux, Docker, Nginx, Exim

Global E-Commerce Platform – Localisation & Warehouse Management

01/2013 – 12/2015, Cologne

Company: [Confidential] – Role: Software Developer & Architect (Full Stack) – Type: Consulting Project

  • Full e-commerce and ERP platform developed from scratch, with a focus on SEO, fast response times, and fully responsive HTML5 layout

  • Localisation and internationalisation implemented for layout, payments, taxes, languages, and currencies

  • Modular architecture designed to support new frontends, e.g., for the Asian market

  • Initial shop themes delivered for DE, RU, ES, and EU (EN)

  • Back-office system developed to manage products, sales, and customers

  • Migration of orders and customer data executed from legacy system to new platform

  • Close collaboration in a small development team to ensure seamless integration and efficient delivery

Tech Stack

  • Languages & Frameworks: Python, Pyramid, JavaScript, AngularJS v1, SQL

  • Frontend: HTML, CSS, Responsive Layouts

  • Databases & Storage: ZODB (File Storage), PostgreSQL

  • Infrastructure & Hosting: Nginx, Debian GNU/Linux, LXC

Before 2015 – Leadership Roles and Early Projects

eTargeting
Insel Project
Express-Kniga
Positiv Multimedia

2005 – 2014

  • Head of IT Department, leading a team of up to 10 people

  • CTO and Software Development Manager at eTargeting (Cyprus), managing a team of up to 10 engineers

  • Senior Software Engineer at Positiv Multimedia (Germany) – Python (Zope, Plone) and PHP

  • Startup & experimental GIS project (PostgreSQL/PostGIS, GeoServer, Leaflet; database administration, replication, backups) – https://mymir.org

  • Automated competitor data monitoring alerts (project)

  • Development of retargeting and remarketing systems for online advertising and lead generation

  • Real Estate Exchange Portal (project)

  • Hosting Solution (project)

  • Python Component Framework (project)

Tech Stack

  • Languages & Frameworks: Python (Python), Zope, Plone, PHP, Java, C, ASP, JavaScript

  • Databases & Storage: PostgreSQL, PostGIS, ZODB, MySQL

  • GIS & Visualisation: GeoServer, Leaflet

  • Infrastructure & Hosting: Debian GNU/Linux, Nginx, Hosting Solutions, Virtualisation (LXC)

  • Networking & Hardware: Cisco (switches, routers), network bonding, BGP, routing & high-availability setups

  • AdTech & Data Processing: Retargeting / Remarketing systems, competitor monitoring, data pipelines

  • Other Tools: Replication & Backup Strategies, Automation Scripts

I began professional software development in 2002 with C, ASP, PHP, and Java, before focusing on Python and Zope for full-stack development and IT. Further projects and roles before 2015 are omitted here for brevity but can be provided on request.

Personal AI-Driven Projects

pois.world — Open map & virtual-parcel platform

pois.world logo

2025 – present

  • Mark any place on Earth with photos, videos, tags, and chat; own ~1M virtual parcels worldwide on a 2.5D / 3D map. https://pois.world

  • A solo, fully AI-agent-driven build — proof that a single engineer plus a disciplined agent workflow can ship a production-grade platform: nine microservices, seven shared libraries, a Rust client core and four clients (web, iOS, Android, Sailfish).

  • Concept → Plan → Spec → Code → Feature discipline; spec / feature registry the agents read from and write back to, referenced in code and PRs — knowledge synthesised across the whole codebase, not stuck in any single developer’s head.

  • Backend: FastAPI + SQLAlchemy 2 async + GeoAlchemy2 on PostgreSQL 17 / PostGIS, Alembic, Pydantic; auth service with RS256 JWT, magic-link and OAuth2.

  • UI: SvelteKit + Svelte 5 (runes), TypeScript, Tailwind, shadcn-svelte, MapLibre GL JS (2.5D), CesiumJS (3D), Turf.js; one JS bundle for web, iOS and Android via Capacitor with self-hosted OTA updates.

  • Native: iOS shell in Swift (UIKit), Android shell in Kotlin / Java, Sailfish client in C++ / QML; App Store and Google Play publishing, APNs / FCM push, on-device e2e (XCUITest, UiAutomator).

  • Rust core: shared client logic (offline write queue, id reconciliation, typed API) compiled once and bound to Swift and Kotlin via uniffi and to the web via WebAssembly.

  • Real-time and media: WebSocket /ws/live over Redis pub/sub, Redis Streams job queue; ffmpeg NVENC video pipeline to DASH / HLS, imgproxy, MinIO object storage; voice input via faster-whisper + LLM over gRPC.

  • Geo services: martin vector tiles, Meilisearch, self-hosted Overpass and Nominatim, terrain / imagery mirror.

  • Payments: Stripe, in-app purchases (StoreKit, Play Billing), Bitcoin.

  • AI: pois-mcp MCP server makes the platform first-class to AI agents.

  • Hosting: self-hosted bare-metal Kubernetes for prod, Incus-VM dev cluster, Docker Compose for local dev; Forgejo git, private registry, observability stack.

Tech Stack

  • Languages: Python, TypeScript, Rust, Swift, Kotlin, Java, C++ / QML

  • Backend: FastAPI, SQLAlchemy 2 async, GeoAlchemy2, PostgreSQL 17 / PostGIS, Alembic, Pydantic, httpx, pytest

  • Frontend: SvelteKit, Svelte 5, Tailwind, shadcn-svelte, MapLibre GL JS, CesiumJS, Turf.js, dash.js, vitest, Playwright

  • Mobile & Native: Capacitor 8 + self-hosted OTA, UIKit, media3 / ExoPlayer, AVKit, XCUITest, UiAutomator, TestFlight, App Store, Google Play, APNs, FCM

  • Rust Core: uniffi (Swift, Kotlin), wasm-bindgen (web), progenitor (typed API from OpenAPI)

  • Data & Messaging: Redis (pub/sub + Streams), MinIO, Meilisearch

  • Media & Voice: ffmpeg NVENC, DASH / HLS, imgproxy, GDAL, faster-whisper, gRPC

  • Payments: Stripe, StoreKit, Google Play Billing, Bitcoin

  • AI / Agents: Claude Code, Cursor, Zed, MCP (Model Context Protocol)

  • Infra & Hosting: Kubernetes (bare metal), Incus VMs, Docker Compose, Forgejo, private registry, martin, Overpass, Nominatim