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• Project management and execution of every stage of the project lifecycle
• Project planning and coordination including detailed project plans, timelines, delivery schedules, risk assessments, and mitigation strategies
• Resource management to meet project deliverables and optimize project profitability

• Design new features in a flagship SaaS product
• Code new features in a flagship SaaS product
• Review new features in a flagship SaaS product
• Test new features in a flagship SaaS product
• Refactor legacy software components
• Participate in large-scale design of the future state of the product

• 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

• High-performance simulation loops, autonomous behavior, and data-oriented design
• Improve system performance, proactively indetify technical debt
• Understanding and optimize complex dataflows
• Designing, improving, extending existing architecture
• Create technical specification based on business needs

• Design, develop, and maintain scalable fullstack applications using .NET and Angular
• Integrate and manage messaging systems such as Kafka and RabbitMQ
• Deploy and manage applications using Docker and Kubernetes in AWS environments
• Work with various databases including PostgreSQL, MSSQL, and Couchbase

Plan and undertake security acceptance tests, execute thorough vulnerability assessments and penetration tests on IT, network infrastructure, applications (including mobile, web and thick-client solutions) on MOL Group level including IT projects, IT-Business projects, Business-IT projects and...

• Application development leadership
• Application implementation oversight
• Application monitoring and issue resolution
• Application maintenance management
• Application support provision
• Data validation against official sources
• Request management for data modifications

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML/MLOps projects
• Ensuring successful execution of cloud migration projects

• Identify AI and automation opportunities across business processes
• Work with different departments to understand processes, pain points and repetitive activities
• Challenge existing ways of working and propose simpler, automated or completely new approaches

• Support aiSim project managers in day-to-day coordination of software development projects
• Work closely with software developers and cross-functional teams
• Record and track meeting minutes in Confluence
• Create and manage Jira tickets
• Communicate with internal and external stakeholders

• 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

• Verification process of IoT, Mobile and Infrastructure subsystems integrating the latest Arm IPs
• Design and verification activities to fulfill project requirements
• Collaboration with architecture, design, verification, performance analysis, implementation and various IP teams

• Participation in the whole lifecycle of development projects from planning to handover
• Maintaining existing cross-platform apps
• Developing cutting-edge projects while writing high-quality code
• Keeping up with the latest technology trends
• Communicating well with other team members

• Writing production-quality, well-tested scraper code in Python
• Learning the architecture of the collection platform including scrapers, proxy layer, queues and enrichment API
• Debugging issues across multiple components using logging, monitoring and alerting tools

• 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

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML and MLOps projects
• Ensuring successful execution of cloud migration projects

• End-to-end AI solution ownership
• Partnership with product managers and business stakeholders for problem translation
• Independent planning and execution of research and experimentation
• Design of AI solutions with system-level perspective

• Dotnet alkalmazások fejlesztése és karbantartása C# és .NET Core technológia használatával
• RESTful API-k és mikro-szolgáltatások fejlesztése
• Adatbázisok kezelése és optimalizálása
• Szoftverek teljesítményének javítása és hibák keresése
• Meglévő kódok refaktorálása

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...