Engineering Manager – Data & AI

Location: Hybrid work in Germany, with Cologne (HQ) or Munich as office options; fully remote work is not available. Willingness to travel up to approximately 30% is required.

Company

KI performance develops data platforms and AI-powered solutions for digital transformation, collaborating with Microsoft, Databricks, and the hirify.global ecosystem.

What you will do

• Design, evolve, and own complex Data & AI systems, including agentic architectures, orchestration, integrations, and governance.
• Define architectural standards and make system-level trade-offs across scalability, cost, reliability, security, and maintainability.
• Take end-to-end responsibility for technical feasibility, implementation quality, go-live readiness, stable operations, and measurable customer impact.
• Contribute hands-on to system design, agent design, protocols, integrations, backlog prioritization, and technical delivery planning.
• Lead, mentor, recruit, and develop senior engineers, domain engineers, and data experts.
• Support strategic customer accounts, pre-sales, solution architecture, feasibility assessments, and technical risk evaluation.

Requirements

• Very senior engineering experience focused on system thinking, architecture, ownership, and production-grade delivery.
• Deep experience with Data, Cloud, and/or AI systems in complex enterprise environments.
• Strong background in cloud-native data and AI architectures, ideally using Microsoft Azure and Databricks.
• Experience designing end-to-end systems involving data pipelines, agent orchestration, integrations, monitoring, and governance.
• Demonstrated ability to lead senior engineers, communicate technical decisions, and align engineering, product, management, and client stakeholders.
• Fluent written and spoken English and German, plus willingness to travel up to approximately 30%.

Culture & Benefits

• Hybrid work model with office options in Cologne and Munich.
• Technical decision authority and end-to-end responsibility for production-grade Data & AI systems.
• Combination of hands-on engineering, people leadership, and business development.
• Culture focused on ownership, clarity, technical excellence, diversity, innovation, and close teamwork.
• Opportunity to influence the productization and scalability of Data & AI offerings.