• Build, configure, and test AI solution components according to architectural designs and business requirements. • Prepare technical instructions, implementation guidelines, and supporting documentation for systems and processes. • Document daily activities, technical updates, and system functions to support delivery transparency and operational continuity. • Coordinate with team members and lead technical tasks as assigned to support successful solution development and deployment. • Participate in troubleshooting, optimization, and enhancement of AI-enabled applications and integrations. • Collaborate effectively within a team environment and communicate progress, issues, and recommendations to stakeholders. • Use applicable technology proficiently to support development, testing, and implementation work.

• Implement and drive the technical direction of the conversational AI solution (KIRA) • Drive delivery and lead the engineering team • Ensure high-quality German-language conversational experiences • Build the technical foundation for broader AI capabilities • Design the technical architecture of the conversational AI solution • Work hands-on on prompt engineering, orchestration design, and evaluation • Define and implement standards for prompting, prompt versioning, evaluation, and quality assurance • Develop scalable AI architecture • Make build-vs-buy decisions • Contribute to the technical roadmap for AI capabilities • Collaborate closely with the Product Owner

• Designing and implementing AI agents with reasoning pipelines (e.g., multi-step workflows, RAG-based decision making) • Integrating AI capabilities such as LLM-powered services, semantic search, and intelligent automation • Contributing to scalable architectures for data- and event-driven systems • Improving, refactoring, and maintaining existing code bases • Designing tasks in collaboration with the Team Lead and Product Owner • Participating in code reviews, architecture discussions, and knowledge sharing

• Design, build, and deploy production AI applications, copilots, retrieval systems, and agentic workflows • Translate business problems into scalable technical solutions using modern AI engineering best practices • Develop backend services, APIs, and application architectures that integrate AI capabilities into enterprise systems • Build multi-agent systems, AI agents, workflow automation, and decision-support systems • Deploy AI solutions into production with appropriate security, observability, monitoring, evaluation, and governance • Design AI systems that integrate with enterprise data platforms, APIs, databases, messaging systems, and business applications • Collaborate with cross-functional client teams including engineering, data, product, architecture, security, and business stakeholders • Experience deploying and operating containerized applications on Kubernetes, including scaling, service networking, resource management, and production monitoring • Contribute reusable accelerators, frameworks, technical assets, and thought leadership that strengthen the AI Engineering practice • Stay current with emerging AI technologies and recommend practical approaches that improve client outcomes