Python developer állások XIV. kerületben (it programozás, fejlesztés)

• Development, governance, deployment, and ongoing enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle, including prioritizing initiatives, influencing roadmap decisions, and ensuring successful deployment into production

• Use formal verification algorithms to formally prove the correctness of complicated logic problems
• Identify key behaviors for verification to write clear testplans for complex designs
• Implement testplans using innovative formal techniques
• Drive tools to realize their best performance

• Architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines
• Building scalable, production-grade LLM services and agentic workflows alongside traditional ML systems

• Support Meridian technical due diligence and transition readiness using AI-assisted software engineering methods
• Analyse OpenStack-style services and surrounding components to map APIs, configuration flows, service dependencies, database usage, and operational assumptions

• 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

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites
• Analyzing model failures and translating findings into dataset or training improvements

• Strengthening Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

• 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 maintain automated pipelines for legacy .NET deployments and modern containerized/Kubernetes workflows
• Automate provisioning and management of infrastructure using Terraform, Ansible, or Bicep

• 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

• Active involvement in the software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms including software models, development boards and shipping products

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

• 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

• Building AI-powered automation for complex cloud engineering environments
• Combining platform engineering, software development and cloud expertise with modern Generative AI technologies to automate parts of the software development lifecycle

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Design and implement automation for storage provisioning, capacity management, and operational workflows using Python, Bash, and IaC tooling
• Drive reduction of manual toil through scripted workflows and self-service enablement

• 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, 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

• 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

• Automatizált UI és end-to-end tesztek fejlesztése webalkalmazásokhoz
• Automatizált UI és end-to-end tesztek karbantartása webalkalmazásokhoz
• Automatizált UI és end-to-end tesztek stabilizálása webalkalmazásokhoz
• Webes tesztautomatizálási keretrendszerek használata és továbbfejlesztése