Python programmer állás, munka

• Translate R&D business and user requirements into effective system, process, and automation solutions
• Design, implement, test, and continuously improve automated workflows, AI-augmented data flows and AI Agents
• Ensure stable data flows, high data quality, and reliable system operations

• 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

Research and development of a multimodal AI assistant that translates natural-language requests into secure actions on real 3D simulation models...

• 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

Design, build, and maintain scalable data platforms and data & AI solutions tailored to business needs, including the development of governance structures and access control concepts...

Drive the Cloud Infrastructure Security function roadmap in alignment with the Product Manager, Tech Lead, and Engineering Manager....

Design and operate scalable workflows for the ingestion, integration, deduplication and harmonisation of heterogeneous environmental observation and research data, including traceable provenance, metadata enrichment and semantic annotation...

• Implement features and workflow enhancements and support the configuration and improvement of ServiceNow modules (e.g., Risk, CMDB, Asset, Change, Incident).
• Help maintain data consistency across Asset, Process, and Risk domains.

• Shape the future AI & GenAI tech stack at ZEISS by mapping state-of-the-art technology to ZEISS business needs – ensuring scalability, maintainability and cost-effectiveness
• Consult teams in Zeiss Digital Partners and beyond regarding AI & GenAI technologies and implementation

• 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.

• Development and maintenance of the data platform’s infrastructure using Terraform
• Implementation and management of CI/CD pipelines for automation of data and AI processes and pipelines
• Automation of provisioning, configuration, and monitoring of resources in AWS

• 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

The design and development of innovative safety contracts will be your core focus, establishing formal runtime interfaces to ensure safe interaction between decision-making and control in autonomous systems....

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

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...

Partner with Marketing: Act as a strategic partner to the Marketing organisation and advocate for data-driven decision-making by effectively communicating AI strategy and its alignment with business objectives....

• Architect complex data flow solutions, enabling transparent, versioned, and fully auditable computations
• Design the data layer by developing metadata and data lineage models fused by semantic graphs and numerical data

Design, develop, and maintain AI agents for manufacturing use cases (e.g. quality inspection, anomaly detection, process optimisation), using machine learning, deep learning, GenAI, rules, and reasoning....

Act as a key expert for SAP S/4HANA data migration projects, with particular focus on Material Master and Production Master (I.e., BOMs, Work Centers, Routings and Production Versions)....

Design, train, and evaluate machine learning models for manufacturing use cases such as quality prediction, anomaly detection, predictive maintenance, and process optimisation, covering the full ML lifecycle from problem definition to performance tuning....