Python fejlesztő állások VI. kerületben (programozó, fejlesztő)

• Design and development of low-level software to integrate new Arm architecture features across Linux, Android, and related userspace components
• Architecture, development, and optimization of core OS subsystems with a focus on performance, power efficiency, and security

• Fejlesztés és telepítés AI-alapú alkalmazások
• Integráció Large Language Model-ekkel üzleti megoldásokban
• Skálázható backend szolgáltatások építése Python vagy Node.js használatával
• Intuitív felhasználói felületek fejlesztése React vagy Angular segítségével

• Development of advanced technical solutions for infrastructure and services expansion and operation
• Preparation of procedures for the complete life cycle of cloud-native based production environment of packet Core including 5G-SA

• Design and implement backend services and APIs
• Develop new features together with Product Owner and Architects
• Optimize performance, scalability and security
• Write unit and integration tests
• Review merge requests and ensure coding standards
• Troubleshoot incidents and perform root cause analysis

Shaping and evolving the architecture of MDO network automation capabilities including reusable automation patterns, interfaces and technical guidelines...

• Architect cloud-native AI applications integrating LLMs vector search and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines model serving and AI agents in production
• Lead cross-functional teams (Full-stack AI Data)

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines

• Komplex üzleti folyamatok végpontok közötti automatizálása Java és Spring Boot alapokon
• Automatizációs megoldások fejlesztése UI és API szinten Selenium, LeanFT és hasonló eszközök bevonásával
• AI-alapú prototípusok, belső eszközök és automatizációk fejlesztése kontrollált vállalati környezetben

• Design and develop scalable cloud security automation solutions across multi-cloud environments
• Build and maintain platform services using modern engineering practices and a code-first approach
• Own and enhance CI/CD pipelines that enable secure, reliable and efficient delivery

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• End-to-end penetration testing engagements across web applications, APIs, cloud environments, binary applications and internal/external infrastructure
• Simulation of real-world attacks to identify security risks

• Leading, mentoring, and empowering a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifact
• Conducting regular 1-on-1s for career development and feedback
• Removing blockers and ensuring team well-being

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Architect and implement scalable AI/ML solutions on Azure or GCP
• Design and build AI solutions for sales use cases such as automated RFP/RFI ingestion, classification, and response generation
• Design and build AI solutions for intelligent document understanding

• Design, build, and maintain robust CI/CD pipelines
• Manage and optimize cloud infrastructure on T Cloud Public, ensuring high availability and performance
• Administer and troubleshoot Linux and Windows systems in production environments

• Building AI-assisted development workflows for code understanding, documentation, build triage, and handover preparation
• Implementing workflow utilities, prompt packs, repository analysis scripts, documentation helpers, and integration adapters

• Strengthen Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

• Service-level analysis of modular cloud software
• Mapping APIs, configuration flows, service dependencies, database usage, and operational assumptions of OpenStack-style services and surrounding components

• Design and implement cloud security controls across AWS, Azure, and GCP
• Build security automation using CI/CD pipelines, Infrastructure as Code, and Policy as Code
• Develop automated compliance checks and remediation workflows