Python developer állások X. kerületben (ai és automatizáció)

• 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

• 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

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

• 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

• 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

Ownership of detection capabilities from idea to customer impact across the AI/ML detection portfolio including threat similarity search, URL reputation, image-based phishing and brand-spoofing detection, web threat classification, and content classification...

• 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

• Architect Zero-Trust environments for LLM-based solutions
• Implement private networking (Private Link), granular RBAC (Entra ID), and automated policy enforcement
• Ensure compliance with enterprise security and audit standards
• Bridge Data Science and Engineering

• 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

• Planning, coordination, and delivery of signal detection and product safety scientist activities
• Support of mentoring of more junior colleagues
• Development of processes, tools, and systems
• Serving as lead on smaller FSP-type projects

• 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

• Development and enhancement of T Cloud Public platform in a customer-oriented manner
• Operation of the built cloud platform
• Solving complex problems in the daily operation of a hyper-scaler's cloud backend
• Building tools to reduce occurrence of errors and improve customer experience

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

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• Designing OpenStack-based network services on the T Cloud Public platform
• Operating OpenStack-based network services on the T Cloud Public platform
• Further developing OpenStack-based network services on the T Cloud Public platform
• Planning automation initiatives using modern frameworks

• 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

• Development, testing, and operation of automation solutions for infrastructure and network services
• Support for project teams during solution development, quality assurance, release planning, and product releases

• 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, and dataset documentation

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources