Backend programozó állások, munkák

• Development and enhancement of T Cloud Public platform in a customer-oriented manner
• Operation of the built platform
• Solving complex problems in the daily operation of a hyper-scaler's cloud backend
• Building tools to reduce occurrence of errors and improve customer experience

• Technical leadership of web platform projects and responsibility for architecture, quality and scalability
• Proactive stakeholder management, bridging the gap between our customers' business and technology departments and our implementation teams

You will be the architect of our map's intelligence, building the brain that powers our next-generation navigation experience. We aren't just finding the shortest path; we're creating a deeply personalised, multi-modal, and predictive routing engine from the ground up. This is a unique opportunity...

• Support technical due diligence and transition readiness using AI-assisted software engineering methods
• Analyse large software repositories to map services, dependencies, interfaces, build flows, and technical risks

• Building infrastructure for FAQs, self-service pages, and chat platform as a primary support channel
• Enabling smarter customer interactions
• Automating solutions
• Helping other teams deliver better support experiences
• Delivering seamless, impactful solutions across all Wise platforms

• Design, develop, and maintain backend services and APIs that support scalable cloud and on-prem systems
• Take part in architectural discussions, prototyping, and evaluating technical feasibility
• Optimize, test, and continuously improve system performance and reliability

Customer-Focused Outcomes: As a Senior SAP AI Engineer (f/m/d), you will be a key driver of customer value delivery, translating SAP AI architectural blueprints into fully functional, scalable, and production-ready solutions. Specifically, you will:...

• Define and evolve data models for R&D entities
• Design and implement robust data pipelines and automated data quality checks
• Improve traceability and metadata management so data can be understood, trusted, and reused across teams

• 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

• 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

You understand our platform architecture, existing systems and tech stack (C#/.NET, MongoDB, Docker, Kubernetes, GCP/Azure) deeply enough to independently plan and ship features....

• Providing technical assistance and guidance to Wise's data engineering and machine learning community
• Owning difficult technical problems
• Participating in the vision for data engineering through documents and conversations
• Getting buy-in from stakeholders and leadership

• Shaping engineering strategy with broad organizational impact
• Driving platform evolution by identifying cross-cutting pain points and leading the design of secure, scalable, reusable solutions built on AWS and modern serverless and microservice patterns

• 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

• 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)

• 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)

• Develop and Implement: Build and maintain platform solutions that improve the reliability, security, and scalability of our Database Platform infrastructure.
• Operational Excellence: Apply cloud infrastructure, networking, and CI/CD best practices to support our operational data storage solutions.

• Setting the technical direction for AI-enabled platform
• Architecting secure, scalable, serverless systems on AWS
• Defining patterns and governance practices for multiple teams
• Guiding AI value addition across the stack
• Mentoring senior engineers
• Leading org-wide design decisions

• Design, build, and deliver scalable full stack solutions using Angular, TypeScript, C#/.NET, and AWS
• Own features from concept through deployment, monitoring, support, and continuous improvement

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...