Senior AI Engineer (Forward Deployed) (all genders)

SeniorHybrid
CompanyKI group
LocationCologne, Nordrhein-Westfalen, Germany
CategoryData & AI
DepartmentKI performance
SenioritySenior
WorkplaceHybrid
Posted2026-03-10
Viarecruitee

Description

🚀 Become our new Senior AI Engineer (Forward Deployed) (all genders)

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.

Your Responsibilities

Understand the Domain

-
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.

Build AI Solutions End-to-End

-
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.

Own Software Engineering Quality

-
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.

Deliver in Customer Environments

-
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.