HR AI and Automation Lead (All Genders)
Skdse · 🌍 Berlin; Munich, Bavaria
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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Sponsor Radar — Skdse
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About the role
At Stark, we forge the future of European and national security through cutting-edge, AI-driven technology and unmatched engineering precision. As a premier defence technology company, our mission is clear: to equip NATO Allies and their partners with next-generation autonomous defence platforms and advanced AI-driven software built to perform in the world’s most demanding environments. We believe that true security stems from relentless innovation. By combining elite engineering talent with agile technology and an AI-native operational culture, Stark turns complex defence challenges into field-tested, multi-domain solutions. Why Join Us? • The software and systems you work on directly protect personnel and defend European and national sovereignty. • You will work alongside industry-leading minds on autonomous systems, advanced propulsion, and secure cyber platforms. • We foster a fast-paced, collaborative environment where bold ideas are supported by serious R&D backing. About the Team You will be part of the global HR Team, reporting to the Team Lead Ops. Your Mission You will own the practical application of AI and automation across HR at STARK. Your goal is to reduce administrative work, improve data quality and give employees and managers faster access to reliable support. You will identify opportunities, build and deploy solutions, and measure their impact across recruiting, people operations and workforce planning. Working with HR leadership, IT, Security, Legal and Finance, you will make these solutions reliable enough for everyday use in a defence technology environment. Responsibilities • Own the HR AI and automation roadmap. Prioritise projects by business value, process readiness, data sensitivity and implementation effort, with a clear owner and success measure for each. • Build and maintain workflows for recruiting handovers, onboarding, employee changes, approval routing and reporting. Select standard automation or AI according to the task and reliability required. • Develop an HR knowledge assistant using approved policies and guidance. Ensure answers reference current sources, respect access permissions and escalate uncertain or sensitive questions to the right person. • Connect HR systems and collaboration tools through approved integrations. Improve data consistency, resolve failed handovers and preserve the authoritative source for each record. • Improve workforce reporting with reliable headcount, hiring and process data. Help HR and Finance reconcile position approvals, recruitment activity and employee records. • Evaluate tools and vendors with IT, Security and Legal. Define access controls, data handling, retention and monitoring before deployment, with accountable human review for decisions affecting candidates or employees. • Test output quality, permissions and failure scenarios. Maintain documentation, alerts and recovery procedures so deployed workflows remain dependable as systems and policies change. • Train HR colleagues and managers, support adoption and report results through time saved, turnaround times, error rates, usage and operating cost. Required Skills • Around five years or more in HR technology, HR operations, business systems or automation, with ownership of projects from problem definition through implementation. • Evidence of AI or automation solutions you have deployed and maintained, including the problem solved, adoption achieved and measurable operational results. • Practical ability to build integrations using workflow platforms, APIs and webhooks. You can troubleshoot data flows and work with technical colleagues on more complex requirements. • Experience applying language models to business workflows, including knowledge retrieval, output evaluation and ap