Jenkins Experts in Berlin

• Led migration to GCP using Terraform, GKE, and GitOps, improving deployment consistency and scalability
• Implemented Datadog observability stack via Terraform and datadog-operator
• Established automated end-to-end tests and on-call processes, improving incident response and service reliability
• Migrated from NGINX Ingress Controller to Kubernetes Gateway API (NGINX Gateway Fabric)
• Migrated stateful services (PostgreSQL and Redis) to GCP, improving scalability and operational reliability

• Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.

• Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.

• Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.

• Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.

• Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.

• 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

• Designed and developed AI-powered document processing solutions using Python, OCR, NLP, and Large Language Models (LLMs) to automate extraction, validation, and classification of financial documents, reducing processing time by 75%.
• Built intelligent multi-stage workflow automation pipelines integrating AI services, machine learning models, and enterprise systems to streamline financial operations and improve data quality.
• Developed reusable AI-driven transformation frameworks capable of processing structured and unstructured document formats (XML, CSV, JSON, TXT, DAT) and normalizing them into unified business schemas.
• Designed and developed Python-based REST APIs and backend services supporting enterprise finance applications and high-volume data processing workloads.
• Built scalable data synchronization pipelines between Oracle CFIN and SQL databases, incorporating machine learning models for cash-flow forecasting and AP/AR anomaly detection.
• Architected and deployed Apache Airflow workflows to orchestrate AI-powered data pipelines, automating end-to-end processing from document ingestion through financial system integration.
• Led the migration of critical enterprise integrations from MuleSoft to Python-based services, improving maintainability, performance, and operational flexibility while preserving complete data integrity.
• Managed the full API lifecycle including solution design, implementation, documentation, deployment, monitoring, and production support for mission-critical financial systems.
• Collaborated directly with finance stakeholders to identify business challenges, define solution requirements, and deliver measurable operational improvements through automation and AI-driven workflows.
• Worked closely with cross-functional engineering and business teams to rapidly iterate on features, improve processes, and drive successful adoption of AI-enabled solutions.
• Provided technical leadership through architecture reviews, technology decisions, code reviews, and engineering best practices across integration and automation initiatives.
• Mentored developers, established coding standards, and contributed to improving software quality, maintainability, and delivery effectiveness across projects.
• Provided production support during critical month-end and quarter-close financial processes, performing root-cause analysis and implementing rapid fixes to ensure system reliability and data accuracy.

• Founded an AI-powered scheduling and business-management SaaS for SMBs, owning technology strategy, architecture, product development, UX, billing and go-to-market execution.
• Architected and shipped a multi-tenant platform with REST APIs, RBAC, CRM, billing and notifications, powering the manager dashboard, admin console, booking experience and iOS/Android applications.
• Led and mentored 7 software engineers, 1 DevOps engineer, 1 QA engineer and 1 UX/UI designer, while remaining hands-on across backend, frontend and product delivery.
• Built AI voice and chat agents using Python/FastAPI, OpenAI and Anthropic APIs, RAG, pgvector and tool calling; integrated Twilio, Google Calendar/Meet, Stripe and Firebase.
• Owned production infrastructure and automated delivery across separate environments using Docker, Nginx, GitHub Actions and Grafana; represented the company at accelerators and international startup events.

Selected stack: Python, FastAPI, Node.js, Vue 3, React/Next.js, React Native, PostgreSQL, Redis, Docker

• Designed and deployed enterprise Retrieval-Augmented Generation (RAG) applications using LangChain, LangGraph, vector databases, embeddings, and open-source LLMs served through vLLM on GCP GPU infrastructure.
• Built agentic AI workflows using LangGraph with planning, reasoning, tool execution, persistent memory, session management, and Human-in-the-Loop approval mechanisms.
• Developed LLM-powered automation systems integrating BigQuery, SQL pipelines, and external advertising APIs including Meta, TikTok, Amazon, Snapchat, Google, and Pinterest, reducing manual operational workflows.
• Architected multi-agent AI systems for enterprise analytics and decision-support workflows, enabling autonomous task execution and intelligent data interactions.
• Implemented retrieval optimization strategies including multi-retriever architectures, semantic search, context optimization, and query improvement techniques, improving response relevance by approximately 40%.
• Engineered structured prompting strategies, function-calling schemas, and validation workflows to improve reliability of multi-step LLM applications.
• Designed scalable AI services using Python, FastAPI, Cloud Run, Pub/Sub, BigQuery, Docker, and cloud-native deployment architectures.

• Drive migration of enterprise authorization platform from Styra DAS to open-source OPA via Skipper (Zalando's Golang-based ingress proxy) integration
• Optimise k8s resources and integrate native Prometheus metrics with OPA
• Migrate from internal monitoring solution to Prometheus CRs + Dash0

Tech Stack: Java/Kotlin, Golang, Python, Spring Boot, AWS, Kubernetes, Docker, OpenTofu, Prometheus, Grafana

• Developed a Flutter app for eID ID card logins
• Focus: Flutter, iOS, eID, AusweisAppSDK, Mason, Keycloak, Agentic Coding, Arc42, Jenkins

• Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
• Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
• Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
• Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
• Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow

• Developed healthcare and webinar platforms using React, Ionic and GraphQL.
• Built scalable frontend applications in close collaboration with designers and backend teams.

OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.

The MiDAS program aims to integrate Generative AI across the entire BBM organization. My role is to enable the eBike division to adopt and leverage Generative AI by collaborating closely with the MiDAS team in India.

Management:

• Enable the eBike division to adopt GenAI through tailored solutions.
• Collaborate with the MiDAS team in India to design solutions for Generative AI use cases specific to the eBike division.
• Coordinate with the eBike teams to integrate GenAI systems, tools, plugins, and services provided by the MiDAS team.
• Plan roadmaps with eBike and MiDAS India team Product Managers for the delivery and integration of Generative AI solutions.

• Implemented Service Tickets functionality for the HOLAWAL Partner Portal, taking full ownership of the epic from architectural design to delivery
• Conducted stakeholder meetings, defined solution approach, and developed a reusable dynamic LWC component that enables configurable flow creation through JavaScript file settings
• Implemented the IP-VPN workflow as a new business product and managed its end-to-end delivery using Salesforce Communication Cloud
• Designed and developed a customer-facing quoting mechanism enabling external customers to view and accept quotes seamlessly
• Localized and enhanced the customer portal by implementing Dutch translations, improving usability and engagement for a major Dutch client
• Designed a quote request submission flow for the customer portal using Balsamiq wireframing tool, ensuring all required details were captured upfront
• Developed an order form flow using Lightning Web Components to capture products, linked services, and service locations
• Configured Salesforce Industries CPQ by modifying existing products, adding new attributes, and implementing validations to enhance product customization and accuracy
• Implemented Apex mocking using the FFLIB library to build efficient, maintainable, and high-coverage test classes

• Manage the development release and update process for a digitized nationwide trade register project "AuRegis".

• Support software in Kubernetes/OpenShift environments, configure management with Kustomize, and implement CI/CD pipelines using Jenkins/GitLab, SonarQube, ArgoCD, and Azure.

• Oversee system release of microservice architecture.

• Build the CI/CD stack from scratch with GitLab CI, integrating integration tests, dependency checks, and security measures.

• Automate deployment onto OpenShift using Kustomize.

• Set up infrastructure components for development, code review, and code quality analysis including SonarQube.

• Integrate GitOps tools such as Kustomize and ArgoCD, using both Azure and private cloud for sensitive data handling.

• Develop Python scripts in Jenkins for cryptostore configuration and system packaging of products and microservices into deployable units.

• Automate delivery to customers and deployment on test systems.

• Create Kustomize manifests for microservices and develop the related automation, treating documentation as code for clarity and reproducibility.

• Serve as technical advisor for the project's first go-live and oversee further deployments as technical rollout manager.