Python programmer állások V. kerületben középiskolai végzettséggel

• Tesztmenedzsment feladatok vezetése a teljes tesztfolyamat szakmai kísérésével az igényfelméréstől a riportolásig
• Követelményanalízis fejlesztőkkel, üzemeltetőkkel és más érintettekkel közösen
• Tesztstratégiák tervezése, tesztelési lépések meghatározása és követése

• Design and maintain automated CI/CD pipelines
• Automate provisioning and management of infrastructure using Infrastructure as Code tools
• Manage health and performance of mission-critical applications
• Implement advanced monitoring, logging, and tracing for legacy and modern services

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

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

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

• Building and maintaining dataset ingestion, cleaning, and versioning pipelines
• Designing and operating labeling workflows including quality control and inter-annotator agreement tracking
• Owning dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• 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)

• Experience in different data science topics including machine learning, LLM, deep learning
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements

• 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

• Operation and evolution of Kubernetes platform
• Building, configuring, and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Design and operation of NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• 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

• 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

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Építés agentic rendszerek
• Munkavégzés Solution Architect-ekkel és LLMOps-szal
• Fejlesztés agent workflow-k LangGraph / LangChain / PydanticAI / CrewAI használatával
• Integráció API-k, adatbázisok és belső szolgáltatások hívásával biztonságosan

• 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

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain
• Analysing and resolving blockers and issues with ETL pipelines and data discrepancies

• 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 build secure infrastructure foundation for AI-assisted software development
• Operate Kubernetes environments hosting AI engineering tools and services
• Implement GitOps and Infrastructure as Code patterns for provisioning and configuration

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines