Senior AI Engineer (Forward Deployed) (m/f/d)

🚀 Become our new Senior AI Engineer (Forward Deployed) (m/f/d)

As a Senior AI Engineer (Forward Deployed), you will lead the hands-on implementation of AI-driven solutions in complex customer environments.

You combine deep expertise in NLP, LLMs, and speech technologies with strong software engineering skills to build robust, scalable, and production-ready systems. Working closely with customers and internal teams, you translate business processes, decision logic, and data flows into real-world AI applications — from intelligent assistants and speech-enabled systems to enterprise-grade integrations on Azure.

This is a hands-on, AI-first, delivery-focused role with strong ownership of technical quality, scalability, and operational excellence.

• Analyze and structure business processes, decision logic, and data relationships.

• Challenge assumptions and refine requirements together with customers and stakeholders.

• Translate complex domain needs into clear, implementable technical solutions.

• Design and implement AI systems with a strong focus on NLP, LLMs, and speech models.

• Build agentic workflows, orchestration layers, tool integrations, and decision logic.

• Develop end-to-end solution flows that combine AI capabilities with backend and platform components.

• Apply structured LLM patterns such as tool calling, schema-validated outputs, retries, fallbacks, and guardrails.

• Integrate AI services into enterprise environments and production systems.

• Actively implement core application and integration logic — this is not a design-only role.

• Build maintainable, testable, and production-ready software in Python.

• Use modern engineering practices to ensure reliability, observability, security, and cost awareness.

• Improve development speed and quality through automation, testing, and AI-assisted engineering workflows.

• Work directly with customers in workshops, implementation sessions, and delivery phases.

• Drive technical solutioning together with Engineering Managers, Cloud AI Architects, and QA.

• Contribute to architecture decisions while maintaining a strong execution mindset.

• Take ownership of successful deployment and integration in real-world environments.