Jakarta Faces (JSF) Experts in Munich
matched in minutes from over 15,000 CVsHire experts who create server-side Java web interfaces, design reusable Facelets views and connect Jakarta Faces applications with CDI, JPA and application servers. Get precise access to vetted, available freelancers who match your project quickly.
Meet FRATCH Experts in Munich, who have recently used Jakarta Faces (JSF)
Markus B.
Last position:
Developer / DevOps, Consulting at A state authority in Baden-Württemberg / FSAS Technologies GmbH
Oracle Project Management and Automation
As part of the project, the operation of an Oracle infrastructure was automated by developing and enhancing Puppet modules and migrating existing Bash scripts to a standardized configuration management solution.
The aim of the project was to standardize and automate administrative processes, improve the maintainability of the Oracle platform, and increase the efficiency and traceability of infrastructure management through the use of Infrastructure as Code.
- Analysis and migration of existing Bash shell scripts to a Puppet-based automation solution
- Development and enhancement of Puppet modules for Oracle environments
- Automation of installation, configuration and operational processes using Infrastructure as Code
- Standardization and optimization of configuration management for Oracle systems
- Creation and maintenance of technical and operational documentation
- Planning, coordination and professional support during project implementation
- Operation and automation of Oracle systems on x86-based Linux server platforms
- Testing and quality assurance of the developed Puppet modules
- Analysis and resolution of technical errors as part of the automation and migration
- Close coordination with specialist departments and infrastructure teams to implement automation requirements
Technologies used: Puppet 7/8, SLES 15, Oracle 19, Oracle Grid, SVN, Windows Server, Confluence, VS Code, Ruby, Bash, Pass
Vitaliy R.
Last position:
DevOps GitOps (temp) at Signal Iduna
- Responsible for Openshift/Kubernetes on-prem administration and developer support.
- Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
- Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
- Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
- Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
- Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.
Christian T.
Last position:
HDI DevOps & Fullstack Engineer at HDI
- Spring Boot Software Engineer
- DevOps Engineer (Kubernetes, Azure DevOps)
Toolstack: Java, Spring Boot, Kubernetes, Helm, GitOps, ArgoCD, Docker, Azure DevOps, CI/CD Pipelines, Git, Postgres
Celso K.
Last position:
SAP Commerce Cloud FullStack Developer at Spar
- Implementation of a GitLab CI/CD pipeline based on SAP Commerce Cloud 2211
- Development of a new B2C shop with Vue, Node and TypeScript to ensure scalability, extensibility and performance optimization
- Integration of Microsoft Azure Event Grid with SAP Hybris
- Implementation of BDD with Cucumber using Gherkin syntax to promote collaboration between development and business teams
- Support and customization of a Spartacus shop
- Technologies/Languages: Java, REST, OData, Behavior Driven Development (BDD), Cucumber, Node, Vue, TypeScript, Spartacus, GitLab CI/CD, Gradle, Maven, Ant, SonarQube
Sascha J.
Last position:
Agile Coach & Partner at Agisolve GmbH – Pragmatic Agility® | Edler & Stiegler GmbH | CTN Consulting
- Create a product and service portfolio delivering a 360 degree approach to digital corporate sustainability covering KPI management, CSRD reporting and sustainable strategy
- Create vision and business case
- Onboard and align business partners, negotiate contracts
- Set up partner network as self-organized agile team
- Co-develop product and service portfolio
- Coordinate sales and marketing, go-to-market strategy and roadmap
Syamala H.
Last position:
Fullstack Developer at BLG Logistics Group
As part of developing this project, various apps were developed for an IBM portal environment based on portlets and Spring Boot services, as well as the setup of a BI platform based on QlikView
Full-stack development of applications, technical analysis, refinement of requirements with the business department, coordination with the customer, DevOps
Team size: 8 people
Technology: Java 11.0, Maven, Git, Spring, Hibernate, JUNIT, Mockito, React, Jira, SQL, Spring Boot, CD/CI Jenkins, Kanban, Rest Api, Oracle
Environment: Eclipse, IBM Rational Application Developer
Alexander N.
Last position:
Security Expert at DAK-Gesundheit
- Pentesting of mobile applications
- Code review
- Gematik audit
- Development of secure software development methods
- Creation of security and test concepts
- Penetration testing of software and architecture
- Vulnerability analysis
- Automation and information security
- Use of Confluence and Jira
- Working with databases, J2EE, JavaServer Faces, Liquibase, Apache, Maven, Mercurial, Oracle Financials
- Documentation and creation of security policies
- Management of software systems, SharePoint, PrimeFaces, Git
- Compliance with security regulations and .NET, AWS, API
- Tools: MobSF, Frida, Android Studio, Drozer, Objection, Azure
Mohamed A.
Last position:
Software Developer at Pass Consulting Group
- Participating in the development of Back (Quarkus) and Front (Angular) modules for Lufthansa travel Website and the “Bahn Project”.
- Providing technical architectures and solutions for the pre-build modules.
- Documenting the whole process of Reservation and Payment for the “Bahn Project”.
- Creating several unit tests and providing assistance for the CI/CD process.
Michael P.
Last position:
Setup Azure cloud, Java development, CI/CD pipelines at Sulzer GmbH
- Migration of a mainframe application (PL/1, zOS) to the cloud (Azure)
- Data transfer from z/OS (USS) to Azure storage (blob containers, file shares)
- Implementation of the mainframe job control in Java
- Mapping of job network dependencies in Control-M
- Performance analysis and optimization measures
- DB2 (z/OS) migration to Postgres (Azure)
- Technologies: Azure (storage, VM, VMSS, Postgres), z/OS (USS), DB2, Postgres, Packer, Terraform, Docker, Jenkins, GitHub Actions, Control-M
- Tools: Eclipse, Visual Studio Code, IntelliJ
Janusz M.
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Discover over 15,000 top freelancers
Statistics of experts using Jakarta Faces (JSF)
Aggregated from the professional profiles of matched freelancers.
Experience
24 years (Germany: 22 years)
Position duration
1.6 years (Germany: 2 years)
Positions per freelancer
16 (Germany: 15)
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
100% (Germany: 86%)
Master's degree or higher
63% (Germany: 50%)
Doctorate
13% (Germany: 5%)
Certifications per freelancer
3 (Germany: 2)
Most common languages
English, German, French
Speak two or more languages
100% (Germany: 96%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Munich using Jakarta Faces (JSF)
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Jakarta Faces (JSF) experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (100%)
- Banking and Finance (70%)
- Automotive (50%)
- Government and Administration (50%)
- Retail (50%)
- Healthcare (40%)
- Manufacturing (40%)
- Telecommunication (40%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Jakarta Faces does
Jakarta Faces, formerly JavaServer Faces and commonly called JSF, is a Jakarta EE framework for building component-based server-side web interfaces in Java. It manages views, user input, validation, conversion and navigation through a structured lifecycle. Companies use it for data-heavy business applications where consistency and maintainability matter.
Applications and interfaces
Jakarta Faces suits internal portals, administration consoles, workflow tools and customer-facing applications with complex forms. Experts use Facelets and reusable UI components to deliver:
- Multi-step forms with validation and conversion
- Role-aware screens and navigation flows
- Data tables, filters and editable business records
- Reusable page templates and composite components
Ecosystem and tooling
Strong specialists work across the Jakarta EE ecosystem rather than treating JSF as an isolated library. Relevant skills include CDI for dependency injection, JPA for persistence, Bean Validation, REST integrations and security configuration. They may also work with PrimeFaces, OmniFaces, BootsFaces or other component libraries, plus Maven, application servers and automated tests.
When companies need expertise
Freelance expertise helps when a legacy JSF application needs modernization, when a team must extend a mature enterprise portal, or when delivery is slowed by complex view logic. In Munich, specialists may support financial services, manufacturing, logistics and public-sector systems, collaborating remotely or alongside local teams. They can also assess whether an incremental migration is safer than a full rewrite.
What strong specialists deliver
Quality work starts with a clear separation between view logic, application services and persistence. Experienced professionals understand the JSF lifecycle, scopes, partial processing, state handling and accessibility implications. They control component-library dependencies, write focused tests and investigate slow requests, excessive view state or difficult navigation without adding unnecessary complexity.
Choosing the right professional
Look for evidence of production work with Jakarta EE applications, not only familiarity with page templates. Ask how the specialist handles validation messages, CDI scopes, security, browser behavior and integration testing. A good professional can explain trade-offs between server-side rendering and alternative Java web approaches, document upgrade risks and communicate clearly with product, design and operations teams.
Frequently asked questions
Questions about Jakarta Faces (JSF)? Start with the answers below.
Jakarta Faces is used to build component-based server-side web interfaces for Java and Jakarta EE applications. It is particularly useful for enterprise portals, workflow systems, administration screens and forms with detailed validation, navigation and data handling.
JSF is the common abbreviation for Jakarta Faces, while JavaServer Faces was its former official name. The technology moved from the Java EE namespace to the Jakarta EE namespace, so project versions and dependencies should be checked carefully during upgrades.
Jakarta Faces provides a server-side component model and manages much of the view lifecycle for the application. Spring MVC offers a more request-oriented approach, while JavaScript frontends move more rendering and state management into the browser. The right choice depends on team skills, existing architecture, interaction needs and migration constraints.
A strong Jakarta Faces specialist usually understands CDI, JPA, Bean Validation, Jakarta Security and REST integration. Experience with Facelets, PrimeFaces, application servers, Maven, automated testing and browser accessibility is also valuable for complete delivery.
Jakarta Faces work can be straightforward for a focused form or complex for a large application with shared templates, custom components and older Java EE dependencies. The relevant experience depends on the codebase, release goals and integration surface, so assess comparable production work rather than relying only on a general seniority label.
Jakarta Faces projects often work well remotely because source code, environments, issue tracking and testing can be shared online. Munich teams should agree on collaboration hours, documentation standards and the expected level of German or English communication, especially when the application supports regulated or business-critical processes.
A JSF application may be a good candidate for incremental modernization when its business rules remain valuable and the main problems are outdated dependencies, slow views or difficult deployment. Replacement becomes more attractive when the user experience, architecture or integration model no longer fits the product, but a specialist should first map lifecycle behavior and hidden dependencies.
Ask a Jakarta Faces professional to explain a real approach to scopes, validation, partial requests, state handling and component-library upgrades. Strong answers connect technical decisions to maintainability, performance, accessibility and testing, and include clear ways to diagnose problems rather than relying on framework-specific shortcuts.
The average hourly rate of freelancers in Munich, Germany who have used Jakarta Faces (JSF) in their recent projects is 95 €, which corresponds to a daily rate of about 760 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Jakarta Faces (JSF) in their recent projects, 100% hold at least a Bachelor's degree, 63% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Munich, Germany who have used Jakarta Faces (JSF) in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 1.6 years.
The most common languages among freelancers in Munich, Germany who have used Jakarta Faces (JSF) in their recent projects are English (100%), German (90%), and French (30%).
The most common industries among freelancers in Munich, Germany who have used Jakarta Faces (JSF) in their recent projects are Information Technology (100%), Banking and Finance (70%), and Automotive (50%).
The most common business areas among freelancers in Munich, Germany who have used Jakarta Faces (JSF) in their recent projects are Information Technology (100%), Product Development (90%), and Quality Assurance (70%).
Main locations of FRATCH Experts, who have recently used Jakarta Faces (JSF)
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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FRATCH CEO
