Senior MES Software Engineer - AI-Driven, Hybrid

Bayer AG

Warszawa

On-site

PLN 206,000 - 246,000

Full time

14 days+

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Benefits offered by this job

Medical care

Flexible benefits

Insurance - life/accident

Pension plan

Home office allowance

Hybrid work model

Job summary

Bayer AG in Warsaw is seeking a Senior MES Software Engineer to drive AI-enabled MES development with Siemens OpCenter. You will design, build, test, and operate scalable MES solutions in a global product environment.

This role blends Generative AI and agentic software practices with cloud-native engineering, CI/CD, and DevOps to raise delivery speed, quality and reliability. Hybrid work options and transparent compensation are offered.

Qualifications

Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Engineering, or a related field.
5+ years of experience in software engineering or related technical roles.
Strong knowledge of Generative AI, Agentic AI, AI-assisted software development, intelligent automation, and modern software engineering practices.
Hands-on experience with AI-enabled developer tools, coding assistants, copilots, or agentic workflows.
Experience identifying and implementing AI-driven productivity improvements within software delivery processes.
Experience with APIs, microservices, cloud-native architectures, CI/CD, DevOps, and software automation.
Hands-on experience with MES.
Experience with Siemens OpCenter or comparable MES platforms.
Experience integrating MES with SAP, LIMS, automation systems, or enterprise platforms.
Familiarity with cloud platforms such as Azure, AWS, or Google Cloud.
Understanding of GxP, validation, data integrity, and security requirements in regulated environments.
Strong analytical, communication, collaboration, and problem-solving skills.

Responsibilities

Drive adoption of Agentic Software Development and AI-assisted engineering practices.
Leverage AI-powered tools to improve software development, testing, documentation, troubleshooting, and knowledge management.
Identify opportunities where AI copilots, intelligent agents, and automation can increase engineering productivity and software quality.
Collaborate with engineering, architecture, data, and product teams to integrate AI-enabled capabilities into software delivery processes.
Evaluate emerging technologies and recommend practical applications that deliver measurable business value.
Ensure AI-enabled solutions are implemented with appropriate governance, security, compliance, and human oversight.
Design, develop, test, and maintain MES solutions based on Siemens OpCenter.
Lead implementation of MES features, enhancements, and technical work packages.
Ensure MES solutions are scalable, maintainable, compliant, and aligned with enterprise architecture standards.
Design MES workflows, services, integrations, and interfaces supporting manufacturing processes.
Develop and maintain integrations between MES, SAP, LIMS, automation systems, and enterprise platforms.
Build APIs, middleware solutions, and event-driven services.
Support integration testing, validation, deployment, and release activities.
Promote reusable integration patterns and standardization across the MES landscape.
Develop high-quality software using modern engineering standards and best practices.
Apply CI/CD, automated testing, Git-based development, and DevOps methodologies.
Support cloud-native and containerized deployment models.
Apply microservices, API-first, and event-driven architectural patterns.
Continuously improve software quality, maintainability, and engineering efficiency.
Support and operate business-critical MES applications and services.
Troubleshoot incidents, perform root-cause analysis, and implement sustainable solutions.
Improve application stability, availability, performance, and resilience.
Contribute to operational excellence and continuous service improvement initiatives.
Collaborate with product teams, manufacturing stakeholders, and business partners to deliver business value.
Mentor junior engineers and promote engineering best practices.
Contribute to technical communities, standards, and capability development initiatives.
Foster a culture of innovation, continuous learning, and responsible AI adoption.