Software development engineer állások XXIII. kerületben (it programozás, fejlesztés)

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• 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

• Design and build agentic systems that plan, call tools and automate real business workflows
• Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration

• Preparation of business concept and business strategy
• Review, analysis and evaluation of business systems, user requirements and processes
• Definition of business goals and KPIs
• Cooperation with developer and testing team
• Participation in User Acceptance Testing

• 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

• Assisting in delivering engaging training sessions and workshops
• Supporting the development of IT courses with lead trainers and technical experts
• Creating and refining educational materials including exercises, tests, and case studies

• Gyártási, termelési, pénzügyi és kontrolling kimutatások, KPI-riportok készítése és fejlesztése Power BI-ban, prezentálás a vezetőség és a társosztályok felé
• A forrásrendszerek adatszerkezetének feltérképezése és dokumentálása

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions with stakeholders
• Set best practices around MLOps and production-grade AI
• Mentor developers and contribute to internal knowledge-sharing

• Design and develop normalized and denormalized data models to support reporting and data integration needs
• Apply dimensional modelling techniques to create efficient, scalable, and business-oriented data models
• Develop and maintain data transformations and models using SQL and dbt

• 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 of custom objects, custom fields, pick list, role based page layouts, workflow alerts and actions, validation rules, approval processes, custom tabs, custom reports, report folders, report extractions to various formats, design of Visualforce pages, record types, dashboards, and email...

• Configure and develop ServiceNow capabilities
• Build and support integrations between ServiceNow and Flexera for asset/license-related data ingestion.
• Build and support integrations between ServiceNow and NetBox for infrastructure and network/OT asset data ingestion.

• 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

• Architect cloud-native AI applications integrating LLMs vector search and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines model serving and AI agents in production
• Lead cross-functional teams (Full-stack AI Data)

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifact
• Conducting regular 1-on-1s for career development and feedback
• Removing blockers and ensuring team well-being

• Definition and development of system-level tests for high-end embedded computing systems
• Automation of test execution and evaluation through scripting in a CI environment
• Increase of test coverage by extending functional examples into comprehensive test suites

• Technical ownership of governance infrastructure supporting the GBS Digital Enablement organization
• Maintenance and continuous enhancement of governance infrastructure
• Ensuring reliability, scalability, governance and accuracy of tools, workflows, data structures and reporting solutions

Process Design & Optimization: Design and continuously improve end-to-end Requisition-to-Receipt (R2R) processes, implementing best practices, automation opportunities, and intelligent workflows including guided buying, supplier punchouts, and catalog-driven purchasing for Direct and Indirect...

• nagy mennyiségű adat feldolgozását támogató adatfolyamatok tervezése és fejlesztése,
• adatbetöltési, adattranszformációs és adatminőség-ellenőrzési folyamatok kialakítása,
• adatforrások integrálása, strukturált és félig strukturált adatok kezelése,