AI Systems Engineer - MLOps & Cloud

AI Integration & Platform Architecture

• Convert software prototypes into high-performance production applications.
• Integrate AI inference services into existing core product architectures.
• Develop and maintain robust REST APIs, microservices, and messaging interfaces.
• Support seamless integration with external software and partner systems.

Operations & Cloud Deployment

• Deploy, monitor, and maintain AI-enabled software systems across AWS and container platforms.
• Collaborate with DevOps teams to establish CI/CD pipelines and containerised deployments.
• Optimise system reliability, data processing workflows, and processing latency.
• Diagnose and resolve integration and interoperability issues across desktop and cloud interfaces.

Cross-functional Collaboration

• Partner with QA, Product, Cloud, and Data teams to drive feature implementation.
• Participate in technical planning and present progress on integration architecture.
• Drive continuous improvement across software workflows and product quality.

An established international developer of specialised software solutions, primarily within health tech and digital systems, is seeking an experienced AI Systems Engineer to bridge the gap between machine learning research and production-grade software. In this role, you will lead the integration of AI models and advanced processing pipelines into desktop, mobile, and cloud environments. Working cross-functionally across engineering, product, and data teams, you will optimise system performance, build robust APIs, and scale secure services across complex software architectures.

Full professional fluency in both German and English., 3+ years of professional software engineering experience.

Strong programming background in Python, C#, or C++.

Proven experience integrating APIs, microservices, and distributed systems.

Hands-on experience with containerisation technologies, orchestration tools, and cloud platforms (preferably AWS).

Foundational understanding of AI inference, data processing, and MLOps practices.

Demonstrated track record of deploying and troubleshooting production software.

Strong analytical, problem-solving, and cross-functional communication skills.

Experience with industry-standard machine learning frameworks, model optimisation engines, or deployment runtimes is advantageous.

Familiarity with enterprise software development or regulated systems is a plus.

Full professional fluency in both German and English.

Key role shaping digital platforms for a global technology innovator.

Exposure to cutting-edge machine learning and cloud architectures.

High degree of ownership, autonomy, and strategic technical impact.

Annual salary and benefits package is available.