Neo4j Experts in Berlin

• Context: Healthcare and laboratory teams required faster document analysis, treatment-planning support, and reliable AI workflows for MR/VR-assisted operations.
• Contribution: Built the AI healthcare platform, model/agent workflows, VR-glasses deployment platform, REST APIs, Next.js/React interfaces, and CI/CD pipelines.
• Impact: Delivered a production-ready AI product foundation that improved clinical document review, supported laboratory automation, and made VR fleet deployment manageable across environments.

Tech: TypeScript, Next.js, Node.js, React, Java, Spring Boot, Python, PyTorch, TensorFlow, Docker, PostgreSQL, OpenAPI, GitLab, GitHub Actions.

• 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

• Developed and implemented organization-wide discovery framework based on Ulwick’s Outcome-Driven Innovation; enabled 7 Product Owners to systematically identify and quantify unrealized value through shared outcome language and opportunity scoring methodology
• Transformed Product Owner role from backlog clerks to strategic experimenters; established dedicated time budget for autonomous hypothesis testing and discovery activities
• Rebuilt customer journey maps to start at actual user need (tool selection phase) instead of platform entry point; eliminated manual data aggregation work previously done by project teams
• Implemented OKR framework across 4 product teams; defined quarterly objectives with measurable key results (e.g., 40% reduction in manual integration effort, self-service adoption increase)
• Unified 3 separate platform roadmaps through cross-team dependency mapping and shared service agreements
• Supported enterprise sales cycle with ROI modeling and technical due diligence for automotive and defense customers

• Develop and demonstrate solutions using GenAI software like langchain, vercel ai sdk, copilotkit
• Work with customers to understand their challenges and provide the best solutions based on open-source data products
• Build RAG and GraphRAG solutions using Neo4j, lancedb, and Postgres
• Deploy a LLMOps platform using kubernetes, terraform, helmfile, Arize phoenix, mlflow
• Architect and build data pipelines using dbt, Trino, Spark, Iceberg, Airflow, ArgoCD, terraform, kubernetes
• Delivered user-centred technical strategy for Agriculture 4.0 and precision livestock farming, helping my client secure funding from Bpifrance
• Delivered a prospecting tool for a leading French solar carport installer, using geospatial computing (GIS), speeding up the sales process
• Built digital twin architecture for solar carports and EV chargers, making real-time monitoring and smart charging possible

Java 21 · Spring Boot 3 · Keycloak · PostgreSQL · Docker · Nginx · GitHub Actions · DigitalOcean · React 18 · TypeScript · Plasmo

• Architected and shipped a production-ready Job Application Tracker end-to-end: REST API with 5-stage workflow, pagination, sorting, and dynamic filtering — full ownership from design to live cloud deployment on DigitalOcean.
• Implemented production-grade identity management: OAuth 2.0 / OpenID Connect / JWT / RBAC via Keycloak, applying Hexagonal Architecture and DDD principles.
• Built automated CI/CD pipeline (GitHub Actions); containerised with Docker; Nginx reverse proxy with path-based routing and SSL termination.
• Developed a Chrome Extension (Plasmo framework, Manifest V3) that auto-fills job applications directly from LinkedIn into the tracker — demonstrates full product thinking across backend API and browser client.

• Developed and maintained Kotlin-based microservices with Kafka event streaming, applying Hexagonal Architecture and Domain-Driven Design in production environments.
• Contributed to the Bring-Your-Salary feature, enabling seamless onboarding of new salary accounts and improving customer experience.
• Built and integrated services for the FPAD VOP platform, supporting secure and scalable partner integrations.
• Investigated and resolved production incidents through root cause analysis (RCA), implementing fixes that improved service stability and reliability.

• Technologies: Java, React, Python, Scala, Spring Boot, JPA, microservices, Kubernetes, Docker, OpenShift, Eureka, Prometheus, Grafana, Zookeeper
• Led the design and development of enterprise wide data warehouse platform for efficient and secure data sharing using stateless, event-driven microservices architecture
• Served as component guardian and Scrum master for three microservices, ensuring seamless integration and maintaining high data integrity
• Optimized performance through Prometheus and Grafana, achieving measurable system resilience

• Conducting counterparty credit risk (CCR) stress testing across a wide range of asset classes, including Listed Derivatives and Securities Financing Transactions (SFTs), ensuring alignment with regulatory requirements.
• Supporting the execution of regulatory stress testing frameworks such as CCAR (Federal Reserve), ECB (Europe), and MAS (Singapore) — including scenario design, results analysis, and full end-to-end coordination.
• Plays a key role in the governance and documentation process for CCAR submissions to the Federal Reserve, ensuring timely delivery, internal signoffs, control evidence, and clear audit trails in line with regulatory expectations.
• Maintains comprehensive, audit-ready documentation for CCAR model assumptions, methodologies, and results interpretation, serving as a point of contact for internal and external audits as well as regulatory reviews.
• Acting as a key liaison during internal and external audits and regulatory reviews, preparing evidence packages, responding to queries, and addressing findings related to CCR stress testing.
• Presenting final stress testing results and key risk drivers to senior management and risk committees to secure executive approval and sign-off prior to regulatory submission.
• Analyzing credit exposure under stress across derivatives and SFT portfolios, identifying and explaining significant drivers.
• Participating in the review and enhancement of CCR methodologies, working closely with Risk Models, Front Office, Regulatory Reporting, and Technology teams.
• Development, implementation and automation of risk reporting infrastructure, improving transparency and controls across the CCR stress testing process.

• Tech-Stack: C#, XAML, WPF, MongoDB, Azure Cloud, Azure DevOps, Resharper, Rider, OAuth2.0, REST, XUnit, NSubstitute, FluentAssertions
• Designed and implemented the IO architecture for improved data flow and efficiency.
• Developed a new desktop application from scratch, improving user experience and functionality.
• Led the implementation of daily stand-ups, software refinements, retrospectives, and project planning.
• Wrote unit and integration tests to ensure code quality and stability.
• Conducted code reviews and mentored junior developers.
• Played a key role in the company's digitalization efforts.
• Managed a team of 4 software developers, providing leadership and direction.