Software development engineer állások XVII. kerületben középiskolai végzettséggel

• NAPI ÜZEMELTETÉSHEZ SZÜKSÉGES FELADATOK ELLÁTÁSA, HIBAJEGYEK KEZELÉSE,
• RENDSZER MONITOROZÁSA, MONITOROZÓ AUTOMATIKÁK RIASZTÁSAINAK FOGADÁSA,
• Részvétel a felmerülő problémák okának kiderítésében,
• Élesítések, telepítések elvégzése,
• Üzemeltetési dokumentációk naprakészen tartása

• 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

• Tackling complex technical challenges focused on scalability, reliability, and speed
• Maintaining a high-performance infrastructure that processes millions of events with low latency
• Collaborating with Data Scientists and Engineers to design and implement cutting-edge feature topologies

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• Understanding new Arm architecture and IP features and their implementation
• Devising promotion of benefits to software ecosystems and resolving adoption issues
• Analysis and deep understanding of software solutions deployed in products, especially major open-source projects such as Linux

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Creation of 3D rigs for different types of objects, animals and characters
• Collaboration with the visual effects supervisor and Lead CG to determine the best possible technical and creative approaches
• Delivery of work within established project targets and high quality standards

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• 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

• Support for development, quality assurance and product management
• Working closely with team members to ensure successful completion of projects and overall support with all roll-out services
• Enabling continuous improvement by providing support when needed

• Real-time decision making with machine learning for risk assessments
• Ownership of risk infrastructure for Instant ACH in the US market
• Cross-functional collaboration with software engineers, data analysts, and data scientists

Munkakörhöz tartozó feladatok ellátása....

• 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

• Scaling the platform that powers primary support channels including self-service, FAQs, and high-traffic chat interface
• Refining and scaling the support ecosystem leveraging Generative AI engine
• Engineering the logic and user experience connecting customers to AI capabilities

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Development of low-level software to integrate new Arm architecture improvements spanning Linux, Android, and related user-space components
• Development and optimisation with a focus on performance, energy conservation, and protection

• Joining junior team assisting with latest projects
• Learning skillset necessary to contribute including working with source code and applying development processes
• Attending online brainstorming sessions regularly
• Learning best practices and key technologies to quickly become productive

• CI/CD pipeline-ok kialakítása, fejlesztése és karbantartása
• Deployment és release folyamatok automatizálása
• Cloud infrastruktúrák üzemeltetése és optimalizálása
• Konténerizált környezetek kezelése (Docker, Kubernetes/OpenShift)
• Monitoring, logging és alerting rendszerek kialakítása és üzemeltetése

• Develop and maintain scalable web applications using Angular or React
• Build and optimize RESTful APIs and microservices using Node.js, Python or .NET
• Define and manage cloud infrastructure using Infrastructure as Code, such as Terraform or OpenTofu

• Design and propose changes to current data systems including migration paths and modernization strategies for legacy architectures
• Define and evolve the target architecture for data platforms covering ingestion, storage, processing, and consumption layers