Python programmer állások, munkák it, fejlesztési vezető kategóriában

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

• Implementing and improving business objects for mobile network infrastructure in backend systems up to the API layer
• Providing a consistent and scalable data foundation for internal systems
• Developing and maintaining business objects including data models, backend logic, and APIs

• Own the end-to-end forecasting and price-elasticity models at the core of our pricing engine — from feature and model research through evaluation, deployment, and continuous monitoring
• Scale the forecasting architecture to meet growing demand for granular, product-level forecasts

• Design and maintain a Commerce-wide engineering metrics framework to track delivery health and team performance
• Review metrics health at team, product, and portfolio level to surface bottlenecks and delivery risks early

• Lead the technical lifecycle of ServiceNow and related governance platforms (IRM, Risk, Change, Incident, CMDB, Asset).
• Ensure configurations are secure, scalable, auditable, and aligned with regulatory standards.

Build enterprise cloud infrastructure that provides European data sovereignty and hyperscaler-grade capabilities. You'll work on SAP Cloud Infrastructure, solving complex distributed systems challenges at scale: multi-region networking, container orchestration, storage systems, and the APIs that...

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Define the data, training, and experimentation environment to enable scalable access to data and compute.

Where you belong: Where you belong: ...

• Understand user's problems
• Write code to solve said problems
• Communicate with users and team members
• Review other team member's code
• Continually improve code and understanding of code
• Work independently at times and with others (pairing) at other times
• Visit company sites to understand processes

• Design and build AI agents and workflows that solve concrete business problems
• Take technical ownership of applied AI solutions - from architecture decisions to engineering standards and code quality
• Build enterprise-grade solutions on modern AI platforms, mainly Azure

You'll deliver the full technical architecture (data model, integration map, deployment topology, security model) for 4+ enterprise HubSpot programs of €150k+ each per year, at Director sign-off quality...

• Single point of contact for the research faculty and group leaders on specialist IT, data and computing needs
• Assessment of research IT needs and their translation into actionable demands
• Onboarding and key user management: making sure that our researchers can work productively from day one

Drive Architectural Strategy & Scalability: Partner across Data Science, Platform Engineering, and Product teams to design the technical architecture, data pipelines, and orchestration systems required for high-traffic AI services. Ensure the ecosystem supports highly available, low-latency...

• Lead develop AI services from PoC to Production
• Lead the development of a best practice framework for AI development (both narrow and GenAI) for all dev streams and teams
• Lead the definition, evolution and drive the setup of infrastructure architecture for the AI applications we are building

• Data assets and strategy: Own pre-training, evaluation and metadata assets, shape their strategy and expand them with new data sources.
• Data roadmap and prioritization: Maintain the short- and long-term roadmap, manage the extraction backlog and coordinate dependencies.

• Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Expand the horizon of what is possible by bringing together rich semantic context with large scale business data

• Lead the architectural vision and strategic direction for AI and machine learning systems across a distributed team in India and Europe.
• Architect unified, scalable and secure AI systems that supports international data sovereignty and regional privacy regulations.

• Build agent loops and orchestration: tool use, structured outputs, business-rule enforcement, graceful failure
• Build the integration layer (via MCP) that lets agents securely call backend systems and business APIs
• Render model output into live, streamed, accessible UI via generative-UI protocols