Python developer állás, munka

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Komplex AI megoldások fejlesztése ügyfelek számára (chatbotok, service botok, LLM-alapú alkalmazások)
• RAG (Retrieval-Augmented Generation) alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal

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

• Design and develop automation frameworks across frontend, backend, desktop, API, and data-driven systems
• Establish testing patterns and best practices for long-term maintainability
• Develop and maintain automated UI and end-to-end test suites using Playwright or Cypress

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Experience in different Data Science topics
• Independent delivery of Data Science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Tervezés, építés és üzemeltetés vállalati szintű Agentic AI platformok
• Műszaki vezetés és mérnökök mentorálása
• Szoros együttműködés ügyfél- és belső csapatokkal
• Biztonságos AI környezetek működtetése szigorú szabályozási és biztonsági követelmények mellett
• Architektúra és szállítás irányítása

• Writing clean, maintainable Python code and automation scripts (bash/shell)
• Building CI/CD pipelines and deployment automation for AI systems
• Creating infrastructure as code and configuration management solutions (terraform)
• Developing APIs, microservices, and event-driven architectures

Owning detection capabilities end to end from problem framing and data through experimentation to models running in production and telemetry...

• 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

• Responsibility for the software architecture including fundamental software engineering non-functional and functional requirements and constraints
• Analysis of business and technical requirements for software platforms and infrastructure

• On-premise IT infrastruktúra üzemeltetése, támogatása és folyamatos fejlesztése
• Linux alapú rendszerek adminisztrációja
• Kubernetes klaszterek adminisztrációja
• Middleware komponensek adminisztrációja
• Automatizációs feladatok megvalósítása és karbantartása

• Implementing and improving business objects for mobile network infrastructure in backend systems up to the API layer
• Developing and maintaining business objects including data models, backend logic, and APIs
• Collaborating with internal stakeholders considering requirements related to external partners

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

• Nemzetközi csapat tagjaként hosszú távú tesztelési feladatok különböző projektekben
• Új automatizálási keretrendszer fejlesztése low-code tesztautomatizáláshoz
• A keretrendszer karbantartása, gondozása és folyamatos továbbfejlesztése
• Innováció és új technológiák aktív bevonása és alkalmazása

• Management of end-to-end software release process including branch management
• Software version control
• Release note documentation
• Communication with internal and external collaborators
• Driving release automation by enhancing CI/CD pipelines
• Defect logging and tracking for releases

• Build and evolve CI infrastructure that validates performance methodologies across cloud, on-prem, and hardware targets
• Design controlled, reproducible test environments that help distinguish real regressions from environmental noise when running and profiling targeted workloads

• Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components

• Building, configuring and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Designing and operating NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• Work with an agile mindset and according to agile methodology
• Collaboration within the team, with other teams in the Domain and Deutsche Telekom, and with software engineers using the cloud platform
• Approach work with a DevOps and continuous improvement mindset