Python developer állások, munkák it programozás, fejlesztés területen

• Lead design, development, implementation, validation, and continuous improvement of automation systems enhancing Inventory Control processes
• Drive automation projects from concept through deployment ensuring delivery on time, within scope, and aligned with business objectives

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

Work in our Data & AI Center of Excellence (DACE) in close collaboration with a diverse team of 45 data scientists and AI engineers from various disciplines...

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Komplex AI megoldások fejlesztése ügyfelek számára (chatbotok, service botok, LLM-alapú alkalmazások)
• RAG (Retrieval-Augmented Generation) alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal

• Monitoring platform and resolving issues reported by monitoring application
• Maintaining availability, integrity and confidentiality of security platforms
• Upgrading, remediating and patching underlying operating systems including Windows, Linux, ESXi, firewalls

• Further development of existing optimization components of the airline management system Netline/Crew or Netline Scheduling area
• Implementation and experimentation on new and efficient optimization approaches
• Recording customer requirements for the commissioning of existing optimization components

• Further development of existing optimization components of the airline management system Netline/Crew or Netline Scheduling area
• Implementation and experimentation on new and efficient optimization approaches
• Recording customer requirements for the commissioning of existing optimization components

• Supporting business and marketing decisions with data-driven solutions
• Developing predictive models such as churn scoring to drive retention offers and product propensity scoring
• Translating business needs into actionable ML and AI solutions across marketing, customer care, and network operations

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• Ownership of architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines including retrieval strategy, chunking, indexing, and monitoring

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• 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

• Designing and delivering engineering solutions for our businesses and customers
• Enhancing our infrastructure capabilities and functions with new and fresh ideas
• Performing and improving QA and Test Automation frameworks

• 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

• 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

• Experience in different Data Science topics
• Independent delivery of Data Science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Together with the team, you drive the development and evolution of vision systems
• You understand, evaluate, and challenge model architectures, neural networks, inference pipelines, and diagnostic toolchains, gradually taking over dedicated development and optimization work packages

• Architect Zero-Trust environments for LLM-based solutions
• Implement private networking (Private Link), granular RBAC (Entra ID), and automated policy enforcement
• Ensure compliance with enterprise security and audit standards
• Bridge Data Science and Engineering

• Evaluate, configure, and maintain the AI development tool stack (GitHub Copilot, custom agents, local LLMs).
• Standardise how AI agents interact and integrate with our internal tools, services, and development workflows with MCP.