AI Solutions Engineer

Job description

Working at Freudenberg: We will wow your world! Responsibilities: Design, develop and implement AI use cases and enterprise AI solutions, including Generative AI applications based on LLMs and AI services, AI services and APIs built with Python frameworks (FastAPI, Flask), RAG solutions with vector databases and retrieval frameworks, agentic and multi-agent workflows, multimodal solutions as well as the integration of AI models, enterprise systems, data sources and MCP-based services; Design and maintain SQL-based data integrations and ETL pipelines, ensure reliable integration between AI services, enterprise applications and data platforms, and support the effective utilization of enterprise data for AI-driven solutions; Build and maintain scalable AI model and inference infrastructure, apply MLOps best practices (deployment, versioning, monitoring, evaluation, lifecycle management), implement CI/CD pipelines and deployment automation, deploy open-source AI models and frameworks, and optimize solutions for performance, scalability, cost efficiency, reliability and maintainability; Deploy and operate AI applications on Microsoft Azure, monitor, troubleshoot and continuously improve productive AI services, implement observability, logging, monitoring and alerting, and ensure high availability, operational excellence and service reliability; Implement AI evaluation, validation, testing and quality assurance processes, establish guardrails, error handling and monitoring mechanisms, ensure compliance with AI governance, data governance, security and operational standards, and apply cloud security, authentication, identity and secrets management best practices; Collaborate closely with business stakeholders, software engineers, data engineers, data scientists and IT teams to translate business requirements into technical AI solutions. Support AI adoption, enablement, training and knowledge sharing across business functions; Create reusable components, templates, standards and best practices for enterprise AI development; Stay current with emerging AI technologies and evaluate their potential business value; Document solution architectures, operating procedures and technical decisions to ensure transparency and maintainability. Qualifications: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Information Technology, Engineering or a related field (preferred); 3–5 years of experience in software engineering, cloud engineering, AI engineering, machine learning engineering or a related technical role; Proven experience in designing, developing, deploying, operating and supporting cloud-based applications and AI services in production environments, Experience working in cross-functional, international engineering environments; relevant cloud, AI or technology certifications are considered a plus; Strong Python software development skills, including API development with FastAPI, Flask or comparable frameworks; Experience with Microsoft Azure cloud services and with designing, developing and deploying AI solutions in production environments; Experience with LLMs, AI APIs and Generative AI applications, as well as with SQL, ETL pipelines and enterprise data integration concepts; Experience with CI/CD, DevOps and deployment processes (GitHub / GitHub Actions / Azure DevOps) and knowledge of MLOps principles and model lifecycle management; Understanding of cloud security, authentication, identity and secrets management as well as AI governance, responsible AI and security concepts; Strong troubleshooting, analytical, operational and documentation skills, combined with the ability to translate business requirements into technical AI solutions; RAG architectures and vector databases, agentic AI workflows and multi-agent systems, multimodal AI solutions, LLM orchestration frameworks, MCP integrations, deployment of open-source AI models, Docker and Kubernetes (AKS), Terraform or Bicep, Microsoft Fabric, Microsoft Copilot Studio, GitHub Copilot, AI evaluation frameworks and model performance optimization, Azure AI Services and observability tools, Microsoft Entra ID and IAM concepts is nice to have; Strong analytical and problem-solving skills combined with strategic and structured thinking; Curiosity, continuous learning mindset, creativity and innovation drive; Ability to work independently as well as collaboratively in global, cross-functional teams; Strong communication and stakeholder management skills with a clear focus on quality, reliability and business value delivery. ‎ ‎ The Freudenberg Group is an equal opportunity employer that is committed to diversity and inclusion. Employment opportunities are available to all applicants and associates without regard to race, color, religion, creed, gender (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity or expression, national origin, ancestry, age, mental or physical disability, genetic information, marital status, familial status, sexual orientation, protected military or veteran status, or any other characteristic protected by applicable law. Freudenberg Business Services SRL