Python developer állások Budapesten (it programozás, fejlesztés)

•Working closely with Test Engineers and Developers to understand product requirements and ensure high quality in releases •Testing Siemens SIMATIC S7 PLC and HMI product families’ engineering systems and hardwares •Executing test cases (manual and/or automated) and analyzing results •Writing and...

• Fejlesztés és telepítés AI-alapú alkalmazások
• Integráció Large Language Model-ekkel üzleti megoldásokban
• Skálázható backend szolgáltatások építése Python vagy Node.js használatával
• Intuitív felhasználói felületek fejlesztése React vagy Angular segítségével

• BI alkalmazások fejlesztése (.NET C#, django – python)
• Enterprise Unit belső szervezetei számára eseti és rendszeres riportok készítése
• EDWH (Enterprise Data Warehouse) fejlesztése és új üzleti tartalmak implementálása
• Power BI riportok és dashboardok készítése
• Adatmigráció

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

• Development and implementation of complex generative AI applications from discovery to deployment
• Establishment of best practices framework for deploying cloud architectures supporting AI agents
• Creation of RAG/LLM evaluation pipelines, embedding strategies, and optimization of prompts/runtime

• 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

• 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

• Development of the test automation framework
• Development of test cases/steps
• Development of test tools
• Integration of testing tools into the automation framework

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• Design and implement cloud security controls across AWS, Azure, and GCP
• Build security automation using CI/CD pipelines, Infrastructure as Code, and Policy as Code
• Develop automated compliance checks and remediation workflows

• Development and fine-tuning of AI models including LLMs, Agentic AI, and Generative AI systems
• Building and deploying robust AI applications and services on cloud platforms
• Design and implementation of efficient AI pipelines from data preparation to model deployment and monitoring

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

• Design, develop, and maintain automated test suites as code using Java
• Create BDD-based automated test scenarios using Cucumber against REST APIs
• Automate API testing for OAuth 2.0 and OpenID Connect (OIDC) authentication and authorization flows using RestAssured or similar tools

• Building AI-assisted development workflows
• Testing AI-assisted development workflows
• Maintaining AI-assisted development workflows
• Implementing workflow utilities
• Implementing prompt packs
• Implementing repository analysis scripts
• Implementing documentation helpers
• Implementing integration adapters

• 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

• 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

• Build and maintain scalable cloud infrastructures using modern services and best practices
• Proactive detection, analysis, and fixing of vulnerabilities and performance bottlenecks in cloud environments

• Lead AI-assisted software engineering activities for Meridian
• Design repeatable SDLC patterns for analysis, validation, documentation, and evolution of complex cloud software stacks

• Oracle, Microsoft SQL Server és PostgreSQL adatbázisok napi üzemeltetése és felügyelete Linux és Windows Server platformon
• Mentések ellenőrzése, visszaállítási feladatok és tesztek végrehajtása
• Felhasználó és jogosultságkezelés, adatbázis objektumok kezelése

• 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