Wellness állások, munkák Budapesten

• Support the transition of accounting processes from various European entities to our Budapest hub.
• Handle a wide range of GL activities including manual postings, inventory adjustments, reconciliations, and provision calculations.

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...

Provide QA and Technical Support to Third Party Manufacturers (TPM) and Contract Manufacturer Organization (CMO), TPM/CMO Operations, Affiliates, and other Stakeholders....

• 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

• 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

• 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

• Build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
• Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production

• 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

• Design and own secure, scalable services
• Guide technical decisions and evaluate trade-offs including AI-driven components
• Architect and deliver AI/agentic product features including LLM integrations, multi-step agentic workflows, tool-use patterns, RAG pipelines, and intelligent automation

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power shared AI services across the platform
• Build secure, high performance microservices and platform components on AWS, owning services end-to-end from implementation through deployment and production monitoring

• Driving technical excellence in products
• Facilitating technical design, decisions, troubleshooting and delivery
• Supporting managers in building world class engineering teams
• Researching new technologies
• Leading technical investigations and developing POCs

• 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

• Leading a global engineering organization across several teams and products within a business domain
• Setting the technical and organizational strategy
• Accountability for delivery, reliability, security, and overall performance of the organization

• Participation in an end-to-end agile team with developers, QA engineers and UX specialists
• Involvement in all aspects of software development from architecture and design to coding, unit and end-to-end testing and data model management
• Designing and implementing new features

• Build and evolve CI infrastructure validating performance methodologies across cloud, on-prem, and hardware targets
• Design controlled, reproducible test environments to distinguish real regressions from environmental noise

• 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

• Design and evolve robust cloud-native services and platforms with end-to-end ownership from ideation and prototyping to deployment, monitoring, and iteration
• Influence technical direction without direct authority by identifying architectural pain points and improving engineering standards

• 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 supporting when needed
• Responsibility for vacation planning of direct reports

• Leading and growing multiple agile engineering teams
• Defining and owning the technical roadmap with stakeholders
• Championing responsible use of AI and automation
• Aligning technical strategy with business goals
• Mentoring and coaching engineers at all levels

• Design and ship production-grade agentic systems
• Take technical ownership of Compliance in a Box (CiaB) AI platform
• Architect and evolve AI reasoning layer and agent orchestration framework
• Build and maintain the GRC Brain (AI reasoning layer) and Agentic Cortex (agent orchestration framework)