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.
Your mission Reporting directly to the CTO, you will define and own STARK's AI strategy, across the product, across internal tooling, and across the entire technical organisation. You'll work shoulder-to-shoulder with Chief Engineers and Engineering Leads, setting a direction they can execute against. On the product side, you'll push the boundaries of what's possible in sensing, autonomy, and robotics for defence. On the internal side, you'll systematically drive AI-powered productivity across every function at STARK. And beyond the company, you'll be our most visible and credible AI voice; the signal that serious AI talent picks up when deciding where to build next. ResponsibilitiesDefine and own STARK's AI strategy across product and internal domains, setting a direction that Technical Leads can execute against
Lead AI stack decisions, model selection, frameworks, MLOps infrastructure, evaluation, and tooling, in partnership with the CTO and Technical Leads, with final technical accountability sitting with you
Act as connective tissue across teams: identify and resolve cross-team AI dependencies, shared infrastructure gaps, and redundant workstreams that individual leads cannot see from inside their own domain
Drive internal AI adoption across STARK, developer productivity tooling, agent and automation infrastructure, and responsible-use frameworks across engineering and operations
Provide technical oversight and challenge across all AI workstreams, asking hard questions on methodology, adversarial robustness, distribution shift, and performance under real operational conditions, without taking over delivery
Monitor the academic and commercial AI landscape and translate relevant advances into concrete strategic inputs for the CTO and programme leadership
Keep AI strategy grounded in operational reality by partnering with programme and product leadership so that what we build maps to real mission requirements, not research for its own sake
Raise the AI bar at STARK: contribute to senior technical hiring, define the AI engineering standard, and build STARK's standing in the European defence-AI community
Represent STARK externally, speak at defence, robotics, and AI venues, publish or present where it serves the mission, and act as a credible signal of the company's technical ambition
What success looks like in the first 12 months:
A single, written, widely-understood AI strategy that Chief Engineers and Technical Leads actively use to make decisions
Internal AI tooling in production use, measurably changing how engineering and operations work day-to-day, not as a pilot
At least one product-side AI capability moved meaningfully forward on your direction
STARK visibly more attractive to senior AI talent than when you joined, with at least one strong hire personally pulled into the pipeline
Degree in machine learning, computer vision, robotics, or a closely related field, or demonstrably equivalent depth through industry research and an open publication or open-source record
Proven experience setting AI technical strategy at a senior level, across multiple domains simultaneously, not within a single team or project
Deep technical fluency in at least one of: perception and sensor fusion, autonomy and motion planning, SLAM/localisation, or multi-agent coordination (C2), with enough breadth to engage credibly across all of them
Strong track record of influencing technical decisions without direct line authority, working through and alongside Technical Leads, not over them
Experience in defence, aerospace, or another safety-critical domain where AI system failure carries real-world consequence; direct UAS or ground-robotics experience strongly preferred
Fluent English; working German is a practical advantage in Berlin or Munich
Eligibility for the required security clearance
An existing network within the European defence AI community
Prior experience in a staff- or principal-level AI role inside a scaling deep-tech or defence company
A public profile, talks, papers, or open-source work, that already signals technical credibility
Comfort operating in a high-autonomy, low-overhead role: setting direction and shaping outcomes without a large dedicated team
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