Software development engineer állások XII. kerületben középiskolai végzettséggel

• 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

• Technical ownership of governance infrastructure supporting the GBS Digital Enablement organization
• Maintenance and continuous enhancement of governance infrastructure
• Ensuring reliability, scalability, governance and accuracy of tools, workflows, data structures and reporting solutions

• Technology architect with T Cloud Public hands-on experience
• Deep expertise in public cloud architecture
• Strong understanding of VPC networking
• Strong understanding of IAM & federation
• Strong understanding of cloud security architecture
• Strong understanding of Kubernetes & container platforms

• 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, build, and operate enterprise-grade Agentic AI platforms
• Own architecture and delivery
• Mentor engineers
• Partner closely with client and internal teams
• Run secure AI environments at scale under strict regulatory and security requirements
• Architect Zero-Trust environments for LLM-based solutions

• 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...

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, 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
• Independent delivery of data science projects
• Engagement with clients to understand business objectives and translate them into technical requirements
• Leading pre-sales technical discussions

• 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

• 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

• Építés agentic rendszerek
• Munkavégzés Solution Architect-ekkel és LLMOps-szal
• Fejlesztés megbízható és folyamatosan javuló rendszerek
• Kivitelezés agent munkafolyamatok LangGraph / LangChain / PydanticAI / CrewAI használatával
• Integráció eszközök és adatok biztonságos kezelése

• 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