Jakarta Faces (JSF) Experts in Munich
for robust Java web applications, matched in minutesHire experts who build and maintain component-based Java web interfaces with Jakarta Faces (JSF), Facelets, CDI and PrimeFaces. FRATCH finds a precise match quickly among vetted, available freelancers.
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: 49%)
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 9 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 9 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 known as JavaServer Faces or JSF, is a Jakarta EE specification for building server-side, component-based web interfaces in Java. It manages view state, request processing, validation, conversion and event handling through a structured lifecycle. Teams use it for business applications where consistent forms, permissions and workflow screens matter.
Core Application Areas
Jakarta Faces is common in internal and customer-facing systems with data-heavy interfaces and established Java backends.
- Business portals with complex forms and approval workflows
- Administration consoles for enterprise systems
- Customer self-service interfaces with validation and secure sessions
- Reporting screens connected to transactional databases
- Long-lived Jakarta EE applications requiring controlled maintenance
Ecosystem And Tooling
Strong specialists work with Facelets views, managed beans or CDI beans, converters, validators and reusable composite components. They may also use PrimeFaces, OmniFaces, BootsFaces or other component libraries, alongside Maven, Jakarta EE runtimes and application servers such as Payara, Open Liberty or WildFly. Familiarity with JPA, REST services, security and relational databases is often essential.
When To Bring In Expertise
Companies typically need freelance support during a migration from JavaServer Faces to Jakarta Faces, a modernization of legacy screens or a release with demanding workflow changes. Munich teams may combine remote delivery with on-site workshops, especially when specialists must understand domain rules, existing deployment processes and stakeholder needs. Clear documentation and reliable German or English communication help keep collaboration efficient.
Signs Of Strong Specialists
The best professionals understand the full Faces lifecycle rather than treating pages as isolated templates. They can trace validation and conversion issues, manage view scope safely, reduce unnecessary server requests and structure reusable components. Look for evidence of disciplined testing, accessible markup, secure authorization and careful handling of state across clustered deployments.
Project Outcomes
A well-planned Jakarta Faces engagement should leave behind maintainable views, predictable navigation and a clear boundary between presentation logic and business services. Specialists can refactor tightly coupled managed beans, improve component performance and document integration points. They also help teams decide when to retain the framework and when a REST-backed frontend or another server-side approach is more suitable.
Frequently asked questions
Questions about Jakarta Faces (JSF)? Start with the answers below.
Jakarta Faces is used to create server-side, component-based web interfaces for Java and Jakarta EE applications. It is particularly useful for forms, validation, navigation, role-based screens and data-heavy business workflows.
JSF centralizes UI state, validation and event handling on the server through reusable components. Spring MVC offers a more direct request-and-view model, while a JavaScript frontend usually provides richer client-side interaction but requires separate frontend architecture and API design.
Jakarta Faces work commonly connects with CDI, JPA, Bean Validation, Jakarta Security, REST services and relational databases. Experience with Facelets, PrimeFaces, Maven and application servers is also valuable for maintaining a complete enterprise application.
A small change may suit a specialist who understands the existing view structure and test process. Larger migrations or performance issues call for someone who has handled the Faces lifecycle, scopes, component libraries, security boundaries and the relevant Jakarta EE runtime in production.
Jakarta Faces projects can usually be delivered remotely when the codebase, environments and acceptance criteria are accessible. On-site sessions can still help with domain discovery, legacy-system access and workshops; teams should agree on remote tools and whether German, English or both are needed.
Ask the specialist to explain a real view lifecycle issue, how scopes affect state, and how they would test converters and validators. Strong answers connect component design with accessibility, security, performance and maintainability rather than focusing only on visual output.
Jakarta Faces is often a practical path for an existing JavaServer Faces application when the team wants to retain server-side components and business logic. A specialist should first review namespace changes, library compatibility, deployment settings, test coverage and the migration path for custom components.
JSF engagements depend heavily on the application’s component libraries, scopes, navigation rules and deployment environment. Before starting, clarify the Jakarta EE version, runtime, build process, authentication model, browser support, release workflow and who owns decisions about broader frontend modernization.
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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Philipp Thomaschewski
FRATCH CEO
