Amazon EKS Experts in Berlin

IOG (IOHK), is one of the world's pre-eminent blockchain infrastructure research and engineering companies.

• Converted a lingering R&D project into a cohesive, production-ready testnet; built and scaled the 35-member engineering team (Core, QA, SRE) to achieve this goal.
• Defined strategic direction and aligned technology development with business objectives as a key member of the leadership.
• Optimized software development processes and implemented agile methodologies, enhancing operational efficiency and code security.
• Delivered projects in a fast-paced startup environment through effective project management and resource allocation.

In a lean, execution-focused environment, I took ownership beyond a narrow engineering lane, shaping and implementing systems across backend, data, and infrastructure. Partnered directly with the three founders in a fast-moving, high-stakes environment, turning strategic priorities into concrete technical decisions and production outcomes.

• Owned core platform development across backend (Django/Rest Framework/Postgres), ETL (Python/Dagster), infrastructure (Terraform/Kubernetes/AWS), and frontend (typescript/react) for a climate-tech SaaS product, driving continuous cross-stack development across five repositories from October 2021 to this day.
• Architected and owned a standalone internal Python scoring framework for CRC assessments, using YAML-driven rules and metaprogramming to enable non-technical users to define complex evaluation logic without hardcoded implementations.
• Built and stabilized ETL and scraping pipelines using Dagster and Scrapfly, improving document ingestion, tagging, retry behavior, deployment flow, and operational resilience.
• Contributed to platform modernization and reliability through Django/Python upgrades, Postgres/RDS and EKS changes, CDN/TLS updates, test and performance improvements, and observability hardening.
• Drove backend engineering for product features, translating requirements into technical specifications, API contracts, data structures, and scalable implementation plans.

• Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
• Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator

• Leading the product lifecycle for sovereign AI platform and operating system teams for enterprise & government clients and internal stakeholders (infra, solution delivery, support, revenue)
• Built and scaled the platform from a 200-user beta to a full rollout of 70K+ members at the Bundesagentur für Arbeit (BA), secured with ISO 42001 and EU AI Act compliance
• Architected the shift to a multi-tenant shared inference, increasing GPU cluster utilization from 20% to 85% and reducing infrastructure cost-to-serve by 40% for SaaS clients
• Shipped model quantization, allowing clients to run advanced LLMs on legacy hardware (A100s GPUs) instead of the H100s, saving upwards of 70% cost per enquiry
• Abstracted complex Helm configurations into a dynamic model manager, reducing the time to install or swap models by ~80%
• Killed an expensive move to build own dashboard service, pivoting to an API-first data strategy that clients can consume directly and saving €100Ks in opex and capex
• Built a safety-first agent marketplace and control plane lighthouse project for a Tier-1 bank, allowing internal teams to deploy autonomous agents within strict regulatory guardrails

• Architected and operated cloud-based data and ML platforms for autonomous driving and parking systems, supporting large-scale (multi PB scale) simulation and vehicle data ingestion.
• Implemented security, compliance, and governance standards across Azure subscriptions and cloud resources.
• Managed GitHub organizations and CI/CD pipelines to improve deployment reliability and developer productivity.
• Contributed to hiring and technical interviews as part of the recruitment panel.

• Consulting an NGO in the field of data center sustainability in publicly funded projects (BMUKN with NADIKI and Federal Environment Agency with SIEC)
• Development of Python APIs and web applications, deployment on AWS/ECS with Terraform
• Collecting power consumption metrics for servers, CPUs, GPUs running AI workloads
• Technologies used: AWS, EC2, ECS, Fargate, CloudMap, VPC, Route53, Lambda, EventBridge, CodeBuild/CodePipeline/CodeDeploy, Terraform, Docker, Linux, Bash scripting, Python, Flask, SQLAlchemy, SQL, MariaDB, InfluxDB, Telegraf, Prometheus, Zabbix, Kubernetes, Letsencrypt, certificate management

• Heycar is a leading automotive platform redefining the used car market through intelligent data pipelines, multi-tenant services, and dealer-focused tooling. I led initiatives across backend architecture, data ingestion, and identity management to enhance scalability, reliability, and developer productivity.
• Ingestion Platform: Designed a unified ingestion platform with YAML-based configuration, enabling new dealer data pipelines to be onboarded without code changes, cutting setup time from ~2 months to 2-3 days and improving scalability by 40%.
• Keycloak Leadership: Acted as the company's Keycloak expert, scaling it for multi-tenant identity management and extending functionality with custom plugins and delegated admin APIs.
• Back-Office Tooling: Developed a back-office application integrated with Salesforce, enabling dealers to manage inventory, convert leads, and handle support requests in real time.
• Multi-Tenant Migration: Collaborated across backend teams to migrate Heycar's core services into a unified multi-tenant cluster, ensuring high availability.
• Frontend CI Optimization: Optimized monorepo delivery by implementing CircleCI dynamic config with NX, deploying only affected UI projects and drastically cutting build times.
• Observability & Mentorship: Enhanced monitoring and release reliability while mentoring backend engineers and improving code review standards.

• Built an AI Research Assistant with RAG, LangChain, LangGraph, and OpenAI LLMs integrated with vector search.

• Built a scalable data platform processing millions of structured records daily from multiple sources, enabling near real-time analytics, dashboards, and secure report exports.
• Supported business decision-making by reducing latency in insights and ensuring data reliability.
• Designed and deployed high-throughput Kafka ingestion pipelines, reliably processing millions of records daily for enterprise analytics.
• Built a Redis-based distributed self-healing task system, reducing manual intervention by ~90% and improving overall platform reliability.
• Improved database write performance, increasing ingestion throughput by ~40% and enabling near real-time data availability.
• Developed high-performance RESTful APIs for multi-dimensional analytics and TopN statistics, supporting enterprise teams in identifying key trends and anomalies.
• Optimized queries with caching, materialized views, and partitioned tables, reducing latency under heavy load by ~80%.
• Integrated application-layer Role-Based Access Control (RBAC) to enforce fine-grained data permissions, ensuring secure API access and compliance.
• Improved Jenkins + AWS EKS CI/CD pipelines for zero-downtime deployments and automated rollback, reducing deployment failures by ~90%.

• Designed, implemented & automated cloud infrastructure contributing to 3 projects in a critical role.
• Lead the teams' effort to implement Kubernetes, GitOps, and CI / CD.
• Enabled customers to follow the GitOps approach and deploy their services via ArgoCD.