Python developer állások VIII. kerületben középiskolai végzettséggel

• Operation, maintenance and scaling of database platforms handling terabytes of data
• Design of scalable, reliable database architectures for different workloads and availability requirements
• Support and optimization of databases including PostgreSQL on AWS RDS, ClickHouse, and YugabyteDB

• PEGA alacsony kódszintű alkalmazásfejlesztés eset típusok, munkafolyamatok és üzleti folyamatok modellezése és megvalósítása a PEGA Platformon
• Újrafelhasználható komponensek készítése több alkalmazásban is felhasználható funkcionális modulok fejlesztése

• Shaping AWS-based cloud architectures and technical decisions for SaaS, PaaS, web application, and enterprise cloud environments
• Design and implementation of Infrastructure as Code solutions using Terraform, AWS CloudFormation, or Pulumi

• Development of neural network compiler for custom NN accelerator hardware in C/C++ environment
• Improvement of performance and finding creative ways to make different Neural Network workloads more efficient
• Proactive exploration of new solutions and ideas for projects and sharing with the team

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling by defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

• 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

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Development and deployment of AI-powered applications using modern software engineering practices
• Integration of Large Language Models into business solutions
• Building scalable backend services using Python or Node.js
• Development of intuitive user interfaces with React or Angular

• Designing security solutions based on BT’s security portfolio technologies
• Implementing security solutions
• Testing security solutions
• Handing over security solutions to service
• Creating value through technology for security design across complex multiple platforms and/or technology areas

• Perform web, network, and infrastructure penetration tests independently.
• Actively participate in red team exercises (e.g., initial access, lateral movement, persistence).
• Document test results and deliver detailed, client-friendly reports.

• 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

• 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

• Identifying, developing, and implementing AI-driven solutions to enhance productivity and decision-making
• Supporting colleagues in creating innovative AI-powered solutions including agents, workflow automations, and analytics tools

• Improvement of repetitive processes using AI
• Organization and checking of data used by the Operations team
• Connecting everyday tools to reduce manual work
• Experimentation with AI tools, chatbots and workflows
• Troubleshooting and solving smaller operational tasks

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

• Technikai menedzsment és fejlesztés a csapat felhő alapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint
• Üzleti logika adatmegoldássá történő átalakítása multinacionális csapatban

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