Power platform developer consultant állás, munka

Lead the design, development, and evolution of suena's backend and API infrastructure—ensuring scalability, performance, and reliability as our platform grows....

implement and maintain software applications and IoT systems on AWS using Python, SQL, and Linux, and continuously optimize application performance and identify areas for improvement....

• Design, develop, and maintain applications.
• Optimize and enhance existing applications and infrastructure.
• Ability/interest to work with machine learning.
• Collaborate and communicate with various teams within the company.
• Ensure all applications reflect our internal policies and standards.

Create robust, scalable, and secure microservices that power our SaaS platform for governance Leverage AWS (serverless or migrations) with C#, .Net and Angular Own services end-to-end (code, deployment, monitoring) Drive architecture discussions Regularly demo to the department Shape AI strategy by...

Design, develop, implement and own products and solutions to improve the security, reliability, and scalability of N26 cloud infrastructure and systems in the workload orchestration domain...

Developing innovative solutions that advance AI/ML systems for mobility services Conducting applied research in Agentic AI, including agent design, orchestration strategies, tool integration, and communication protocols Conducting research on AI safety and alignment topics Identifying research gaps...

• System Ownership & Lifecycle:
• Own the entire system life cycle
• for our public cloud-based infrastructure, including requirements gathering, architecting, vetting, building, and operational management.
• Automation & Operational Efficiency: Drive significant improvements in
• operational efficiency

• Collaborate with cross-functional teams to define data requirements and ensure data quality
• Support the data engineering team in reconciling data between the new and the legacy systems
• Participate in monitoring, troubleshooting, and resolving data processing issues

• Implementation of software solutions for research purposes
• Translation of research code into robust software (e. g., optimization, refactoring)
• Contribution to research projects to allow deployment (containerization, virtualization)