UFORCE exists to make aggression unaffordable.

Founded in Ukraine and headquartered in London, UFORCE is a defence-technology company with operations across Europe, the United States and Asia.

UFORCE builds uncrewed vessels, ground robotics and aircraft, autonomy software, and the command-and-control layer that operates them together. Each platform is deployable on its own, and stronger as part of the system. Its product lines include the MAGURA family of uncrewed surface vessels, the NEMESIS family of strike platforms, the LIUT family of ground robotic platforms, and counter-UAS systems.

About the Role

The G&A AI Builder helps Finance, People, Legal, and other internal teams spend less time on repetitive work such as checking numbers across systems, chasing approvals, and rebuilding reports. Starting with Finance, you’ll find the highest-value problems technology can solve and build practical tools — including shared data views, automated approvals, dashboards, and AI-enabled workflows.

You’ll work directly with functional teams to understand their systems, data, business rules, and priorities. You’ll build most solutions yourself, partner with engineers when deeper technical work is needed, and take each solution from discovery through testing, adoption, and measurable impact.

You’ll be successful when teams use what you build, work gets done faster, and UFORCE can grow without the same growth in manual work, software, vendors, or headcount. This is a hands-on role for someone who combines strong business judgment with the ability to turn ambiguous problems into useful solutions.

What You’ll Do

Build a trusted view of Finance actuals, cash burn, expenses, and budget performance by mapping priority systems, aligning definitions, identifying trusted sources, and reducing manual reconciliation.

Launch recurring cash-burn and expense reporting from Payhawk, then expand the shared data approach to actuals, budget-versus-actual tracking, and leadership reporting as additional systems become available.

Help Finance spend less time assembling reports and more time planning and making decisions through dashboards, analysis, and AI-assisted views.

Give People a reliable company-level view of headcount and hiring information, including workforce areas missing from central reporting.

Improve high-friction recurring People workflows such as recruiting operations, hiring analytics, onboarding, follow-ups, reminders, and compliance-related tasks where the evidence supports it.

Help Legal and Compliance move high-value repeatable checks, tracking, and follow-up into clear, auditable workflows, including embedding policy-compliance checks into the software approval process where appropriate.

Discover and prioritize opportunities across G&A by understanding how work actually happens, establishing a baseline, and selecting the problems with the greatest business impact.

Redesign processes around what technology can now do, build the simplest useful solution, put it in front of real users quickly, and improve, scale, or stop based on measurable results.

Partner with Director of Business Data & Intelligence on architectural direction for larger or cross-system solutions, and involve engineering, security, or human reviewers when the complexity, risk, or sensitivity requires it.

Drive adoption so useful solutions become part of normal operating workflows, with documented before-and-after impact such as reduced manual effort, faster turnaround, improved decision-making, or reduced software and vendor pressure.

Required Skills

Hands-on AI building: You personally use AI deeply and have built useful tools, agents, automations, analyses, or workflows. You can show what you built, what failed, how you improved it, and whether people used it.

Business and financial judgment: You understand how companies, numbers, processes, approvals, and reporting work well enough to make sense of messy functional problems and determine which information should be trusted.

Data fluency: You are comfortable inspecting data, connecting information across systems, reconciling conflicting definitions, and turning data into useful analysis or reporting. You do not need to be a data engineer.