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