AI solution architect (m/f/d)

ROHDE & SCHWARZ GmbH & Co. KG; München; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

A leading technology company in Munich is looking for an experienced AI Solution Architect to design and implement scalable AI solutions. The role includes providing technical leadership, evaluating AI tools, and managing stakeholder communications. Ideal candidates will have proven experience in AI architectures and a proactive approach to evolving standards for AI development. This position offers competitive compensation and opportunities for team leadership.

Qualifikationen

• Proven experience in AI solution architecture and design.
• Strong technical leadership and mentoring abilities.
• Expertise in AI technologies and tools relevant to business needs.

Aufgaben

• Develop comprehensive AI solution architectures.
• Provide technical leadership to engineering teams.
• Evaluate and recommend appropriate AI technologies.

Jobbeschreibung

Responsibilities

• Solution Design: Develop comprehensive AI solution architectures for a variety of business problems, encompassing data pipelines, model training/deployment, infrastructure requirements, security considerations and general cost efficiency.
• Technical Leadership: Provide technical leadership and guidance to engineering teams throughout the AI solution lifecycle.
• Technology Evaluation: Evaluate and recommend appropriate AI technologies, tools, and platforms based on business needs and technical feasibility.
• System & Workflow Integration: Ensure seamless integration between AI solutions and existing Rohde & Schwarz systems.
• Scalability & Performance: Architect AI solutions for scalability, performance, and reliability, ensuring they can handle large volumes of data and user requests.
• ML / AI Lifecyle Management: Pro-active mindset to evolve standards and best practices for AI development, deployment and governance (e.g. MLOps, LLMOps, AgentsOps) across Rohde & Schwarz.
• Cost Optimization: Design cost-effective AI solutions, leveraging cloud resources and optimizing model performance to minimize infrastructure costs.
• Documentation & Standards: Develop and maintain comprehensive architectural documentation and establish standards for AI solution development and deployment.
• Stakeholder Management: Effectively communicate architectural designs and technical concepts to both technical and non-technical stakeholders.
• Team Leadership & Mentoring: Guide data scientists, ML engineers, and developers in implementing AI solutions and promote best practices in AI development and deployment.