STARK is seeking a Team Lead Operations Automation & AI to build the automation and AI capability for operations from the ground up across production in Munich. You will own delivery of automation projects, map and prioritise opportunities by feasibility ROI and risk, and build and mentor the Automation Engineer and Data/ML Engineer. Define the team's architecture and toolchain including RPA, LLM-based tools, ML models and API integrations. You will translate pain points into deployable solutions while collaborating with IT and Production Engineering to ensure readiness. To apply, emphasize 8-12 years of automation and AI deployment, ROI, and demonstrated leadership, with deployments and impact across OT and IT.
STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop, and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective — providing operators with a decisive edge in contested environments.
We are focused on delivering deployable, high-performance systems — not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe, today.
Map and prioritise automation opportunities across production and back-office — ranked by feasibility, ROI, and implementation risk
Own end-to-end delivery of automation projects: scoping, design, build, test, production deployment, and monitoring
Build, mentor, and manage the Automation Engineer and Data/ML Engineer
Define the team's technical architecture and toolchain — RPA, LLM-based tools, ML models, API integrations
Work with operational and back-office stakeholders to translate process pain points into deployable solutions
Own the collaboration boundary with IT and Production Engineering
Track and report on automation impact: manual hours reduced, error rates, throughput, cost savings
BSc/MSc in Computer Science, Electrical Engineering, Mechatronics, or Industrial Engineering
8–12 years in automation, industrial digitalisation, or AI/ML — covering both operational and business process automation
Has personally deployed automations in production environments — not just designed or prototyped them
RPA platforms — UiPath, Power Automate, or equivalent
ML/AI deployment — model productionisation across structured operational and unstructured back-office data
Systems integration — API design and data exchange across ERP, MES, and business applications
People management and technical mentorship
Experience across both OT (operational technology) and IT/business process contexts
Industry 4.0 track record — smart factory, MES integration, or similar
LLM-based tooling — prompt engineering, agent design, document processing workflows