Process Automation Experts in Berlin

I served as the Lead Designer for two cross-functional teams at Casavi, a software platform for property managers. Casavi is a central platform for all aspects of digital property management, which streamlines operations and business processes.

SmartTask: The team focuses on ticket management, workflow automation, AI integration, enhancing communication between property managers and their clients.

Customer app/portal: The team is dedicated to fostering community engagement among residents of managed properties. The customer portal in combination with the Casavi app solves the challenges for property and facility managers.

My role spans the full design lifecycle, covering UX/UI design, user research, usability testing, and strategic design planning, across Casavi's web platform, mobile app, and customer portals. Each team comprises around 10 members, including a project manager, designer, developers, and QA testers. I am also responsible for the accessibility assurance of the whole product.

Design unit role: In addition to my core responsibilities, I actively contribute to the development and maintenance of the company's design system and style guide ensuring consistency and scalability across all products. Mentor junior designers is my official and moral responsibility.

• Partnered with senior stakeholders across AWS EMEA to drive talent strategy, partner development, and business growth in the cloud ecosystem.
• Focus areas:
• Collaboration with Sales & Partner Management on Go-to-Market initiatives
• Advisory on long-term resource strategy for Cloud, Data, and Security Divisions
• Supporting internal innovation teams in scaling AI and automation projects
• Result: Contributed to AWS’s expansion in Central Europe by aligning business, technology, and people strategy.

Driving AI model quality at scale — evaluating prompt-response accuracy, flagging edge cases, and maintaining SLA-compliant workflows across distributed global teams.

• Analyse AI prompts and side-by-side model outputs to assess response quality, factual accuracy, relevance, consistency, and compliance with project evaluation guidelines.
• Perform fact-checking, data validation, troubleshooting, issue identification, and edge-case review to improve quality standards across AI training support workflows.
• Use Google Sheets, Google Docs, and browser-based tools to document findings, maintain evaluation logs, track issue patterns, and support workflow optimisation in a remote environment.
• Create clear written justifications, review summaries, and KPI-oriented reporting focused on accuracy, turnaround time, documentation completeness, defect identification rate, and SLA adherence.

• Independent training in travel expense accounting (Egencia, Perk, AirPlus)
• Interface management between travel expense tools
• Onboarding and offboarding of employees and vendors
• Advising teams on posting incoming and outgoing invoices
• Documentation and process improvement

• Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
• Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
• Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
• Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
• Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
• Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
• Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
• Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
• Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
• Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices

• 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.

• Led development of RunBot AI assistant autonomously using LLM-powered workflow automation (React, TypeScript, Java, MongoDB, NATS)
• Architected TMS platform providing unified transportation management and real-time logistics visibility with AI processing pipelines
• Designed event-driven microservices architecture supporting marketplace
• Drove architectural decisions and technical leadership across full-stack platform development

• Analysis of complex business processes and end-to-end user journeys in digital product and platform environments
• Gathering, structuring, and prioritizing business and technical requirements (Functional / Non-Functional Requirements)
• Translating business goals into actionable requirements, user stories, and acceptance criteria
• Conducting stakeholder interviews, workshops, and reviews with business teams, IT, UX, and management
• Creating and maintaining requirement artifacts (BRD, FRD, user stories, process models, decision papers)
• Ensuring consistency between business needs, technical implementation, and product vision
• Close collaboration with development teams to clarify business questions during implementation
• Support with impact analyses (A/B tests), change requests, and scope management
• Quality assurance of implemented requirements including acceptance criteria and business testing
• Advising on the further development of product strategy and roadmap structure
• Prioritizing backlog items based on business value
• Defining and sharpening product goals, KPIs, MVP definition, and other success metrics
• Evaluating new features, tools, and initiatives from a user and business perspective
• Facilitating decision-making between business, product, and technology
• Supporting go-to-market considerations and product positioning
• Sparring partner for product and stakeholder decisions at management level
• Dashboard creation, data modeling, BI report administration, and data analysis in Power BI

• Full automation of the software development process: ticket analysis → AI coding agents → pull request → automated code review → deployment
• Multi-tenant architecture with 82 database models and real-time WebSocket monitoring
• Integration of 40+ AI tools with Claude & GPT
• Tech stack: React, TypeScript, Express.js, PostgreSQL, Redis, BullMQ
• Platform in productive use with paying customers

• Led the project to introduce AI tools for creative teams for image, video, and text creation (Yuma, Google, Flux, cogniwerk.ai, comfy.ai)
• Relaunched Asana and rolled it out to 100 users for shared workflow management and KPI reporting
• Managed the pilot project for the creative workflow automation tool Bannerflow
• Contributed to the overall marketing restructuring project focused on organizational structure and processes

• Planning and implementing tailored Odoo ERP solutions to support and optimize specific business processes
• Configuring and customizing Odoo modules according to individual customer requirements, including process automation and data integration
• Training and supporting end users and administrators to ensure full use of Odoo features and to enhance user skills
• Providing ongoing post-implementation support, including troubleshooting, maintenance and updates to adapt to new business requirements
• Migrating data and integrating external applications into Odoo environments for a seamless, unified data landscape
• Analyzing and improving existing Odoo systems to boost efficiency and optimize the user experience

• Project volume in €: ~15 million
• Number of employees: 8
• Managing strategic projects & leading procurement
• Outsourcing standard products abroad
• Process optimization in quality management
• Interim manager for purchasing & procurement
• Planning and implementation of optimization measures
• Material flow in production
• Warehouse management
• Process automation

• Consulting, coaching, workshops, and project management focused on transformation, potential development, and sustainable growth

• Designed, managed, and implemented the company’s operational, compliance, procurement, and financial strategy, ensuring alignment with rapid scaling and regulatory objectives.
• Built and scaled operational infrastructure across IT, HR, Finance, Procurement, and Compliance, supporting growth from 4 to 20 team members in 6 months.
• Oversaw financial management of OPEX, including budgeting, monitoring, and cost optimization to sustain high-growth operations.
• Developed and executed a procurement strategy, including vendor selection, negotiation, and performance oversight.
• Procured and managed external consultants (compliance, quality, regulatory experts) and orchestrated collaboration across internal teams and external partners to meet milestones.
• Implemented policies, SOPs, and business systems (compliance tracking, eQMS, payroll, vendor management, data governance) to support regulatory compliance and scalability.
• Managed and actively oversaw regulatory and compliance programs, embedding GDPR, HIPAA, SOC 2, ISO 27001, and ISO 27701 requirements into day-to-day operations.
• Directed the rollout of a Quality Management System (QMS) aligned with ISO 13485 to prepare for medical device and AI regulatory certifications.
• Led people and culture development, establishing onboarding, performance management, and cross-functional collaboration structures to scale the organization effectively.
• Established risk management and business continuity frameworks, including security controls, risk registers, and compliance safeguards.
• Engaged executive leadership, board, and investors to align operational strategy with corporate goals and market expansion.
• Enabled technology-driven operations, selecting and implementing digital systems (e.g., Drata, Qualio) to ensure compliance and efficiency.
• Scaled StratifAI’s operational backbone to support rapid growth and international market readiness.
• Achieved ISO 27001, ISO 27701, SOC 2, GDPR, and HIPAA compliance within 6 months, enabling enterprise and healthcare partnerships.
• Implemented a QMS system aligned with ISO 13485, paving the way for regulatory approvals and positioning for upcoming ISO 13485 certification, CE-IVDR marking, and FDA clearance within 12 months.
• Designed and executed governance, procurement, and financial controls, ensuring efficient resource allocation and sustainable compliance.
• Established a culture of structured growth, integrating people, processes, and compliance frameworks to maintain operational excellence.
• Enabled StratifAI to confidently enter regulated US and EU markets, building the foundation for long-term expansion.