Software development engineer állások XIX. kerületben középiskolai végzettséggel

• Design, develop, and maintain backend services and APIs that support scalable cloud and on-prem systems
• Take part in architectural discussions, prototyping, and evaluating technical feasibility
• Optimize, test, and continuously improve system performance and reliability

• Designing and developing Java-based backend microservices
• Building scalable distributed systems
• REST and event-driven communication
• Network provisioning and orchestration workflows
• PostgreSQL modeling and optimization
• CI/CD pipelines and containerized environments
• Kubernetes / Docker infrastructure

• Development and ownership of process training materials for assigned portfolios using the Assima authoring tool
• Maintenance and continuous updates of existing training assets across Product Increment cycles
• Quality assurance and governance of training assets to meet ASPIRE standards

• Producing code to a high standard
• Owning feature development for web-based graphics tools, broadcast control panels, and interactive overlays
• Managing code releases safely across Dev, Test, Staging, and Production environments
• Using APIs efficiently to GET and POST complex tracking data structures

• Producing clean, functional code following established team patterns
• Building and refining UI components for dashboards, charts, and data tables
• Integrating frontend applications with data infrastructure handling JSON data structures

• Producing code to a high standard
• Owning feature development for heavy-duty analytics dashboards, charts, and tables
• Managing code releases safely across all environments including Dev, Test, Staging, and Production

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Building and operating scalable data ingestion and CDC capabilities on Azure-based Lakehouse platform
• Developing pipelines in Azure Data Factory and Databricks
• Maturing engineering approach through Python projects and reusable frameworks

• 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

Support Meridian technical due diligence and transition readiness by using AI-assisted software engineering methods to understand OpenStack-derived cloud services...

• Design, develop, and implement complex and scalable data solutions on the AWS cloud platform
• Design, build, and optimize data pipelines to ensure efficiency and reliability
• Write clean, efficient, and maintainable SQL and Python code
• Develop and maintain shell scripts to support automation

• Analysis of payment and fraud data
• Ownership of performance, tuning, and optimization of fraud detection systems and tools
• Development and maintenance of strong relationships with key stakeholders, internal departments, and vendors

• Participation in an end-to-end agile team with developers, QA engineers and UX specialists
• Involvement in all aspects of software development including architecture and design
• Writing code, unit and end-to-end tests
• Managing data models
• Designing and implementing new features

• Cobol alapú rendszerek fejlesztése és karbantartása
• Üzleti logika implementálása nagyvállalati környezetben
• Rendszerek működésének megértése és optimalizálása
• Hibakeresés és problémamegoldás
• Együttműködés modern technológiákkal dolgozó csapatokkal

• 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 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

• 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

• Automatizált UI és end-to-end tesztek fejlesztése, karbantartása és stabilizálása webalkalmazásokhoz
• Webes tesztautomatizálási keretrendszerek használata és továbbfejlesztése (pl. Playwright, Selenium, Cypress)
• Tesztek integrálása CI/CD folyamatokba

• Coordinating and assigning QC requests to in-house or external linguists
• Tracking the progress of freelance QC projects to maintain quality, delivery schedules, and budget adherence
• Managing daily communication with QC clients regarding project status

• Build and operate multi-cluster containerized environments across cloud platforms
• Create end-to-end CI/CD pipelines for cloud-native applications and machine learning workloads
• Lead cost-optimization and FinOps initiatives for GPU, storage and data-egress spend