About Us
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.
About the team
*The Operations Excellence team sits within the COO organization and serves as a strategic partner to managers, team leads, and colleagues across Stark. By delivering data-driven insights, leading critical projects, and driving continuous process improvement, we help the organization operate more efficiently, scale effectively, and achieve its goals faster.*As an individual contributor, you will take end-to-end ownership of complex initiatives with significant business impact. Working closely with cross-functional stakeholders, you will have the opportunity to influence key decisions, shape core operating processes, and contribute directly to the success of one of Europe’s fastest-growing unicorns.
Your mission
As OAA Lead, you build the automation and AI capability for operations from the ground up — across production and the back-office. You identify where automation and AI deliver the highest ROI across the entire operation, own the technical delivery end-to-end, and build a team that ships working automations into production, not just prototypes.
Responsibilities
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
Qualifications
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
Nice to have
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
