Action1 is an autonomous patch management platform trusted by many Fortune 500 companies. Cloud-native, infinitely scalable, highly secure, and configurable in 5 minutes, it just works and is always free for the first 200 endpoints, with no functional limits. By pioneering autonomous OS and third-party application patching, Action1 helps organizations eliminate routine work, reduce ransomware and security risks, and protect the digital employee experience. It provides real-time vulnerability assessment and remediation across remote and on-site endpoints without requiring a VPN, while peer-to-peer patch distribution reduces bandwidth use on local networks. In 2026, Action1 was recognized as the fastest-growing founder-led cybersecurity company in America on the Inc. 5000. Action1 is led by industry veterans Alex Vovk and Mike Walters, American entrepreneurs who founded Netwrix, which has grown into an industry-leading, multibillion-dollar cybersecurity company.The RoleWe are looking for a senior Applied AI Engineer to join Operations and improve how our business teams work. You will work directly with Support, Finance, Sales Ops, HR, IT, and Legal to turn repetitive tasks and disconnected workflows into reliable AI-powered tools and automations.We build AI to solve real problems, not to follow hype or impress investors. You will investigate how work gets done, propose improvements, and own technical decisions and delivery. We expect you to take initiative, deliver useful results quickly, and improve solutions through short iterations and feedback.What You'll DoWork with teams to understand their workflows, find bottlenecks, and propose improvements. Agree process changes with the COO and relevant teams before implementationBuild AI tools and automations that connect business systems and handle tasks such as document processing or ticket triage. Deliver working versions quickly and improve them through feedbackPrioritize opportunities by time saved, error reduction,



and risk. Measure whether solutions deliver those benefits, reduce costs, and are actually usedRun and support what you build. Test AI outputs, keep integrations reliable as systems change, and manage failures, latency, and costProtect customer and employee data through limited access, minimal exposure, and redaction before model calls. Work with IT and Security on safeguards, audit trails, and human review where neededEvaluate AI tools and vendors, and recommend when to use an existing solution versus building oneDocument workflows and runbooks, train teams to use the solutions, and help them identify and request further automationsWhat we're looking for4+ years in operations engineering, business systems, automation, or a similar role, with 1+ years building production LLM or AI-enabled workflowsHands‑on experience with workflow automation platforms and REST APIs, webhooks, JSON, and OAuthStrong working knowledge of prompt design, retrieval-augmented generation, and agent/tool‑use patternsProficiency in Python or JavaScript, and comfort with cloud services; AWS preferredExperiencewith at least one major business system, such as NetSuite, Salesforce or ServiceNowAbility to translate business needs into technical solutions and explain trade‑offs to non‑technical leadersSound judgment and practical knowledge of AI security, privacy, and data governance, including least‑privilege access, sensitive‑data protection, data minimization,



and approval controls for sensitive actionsNice to haveExperience with Microsoft 365 / Teams integrations and Microsoft GraphBackground in finance, revenue, or support operations processesFamiliarity with process mining, BI tools, or SQLExperience with SOC 2, ISO 27001, or similar compliance frameworksRelevant AWS, Azure, or security certificationsFamiliarity with IT management, RMM, or endpoint security conceptsExperience shipping software with coding agents such as Claude Code or Codex, including harnesses, development loops, reusable skills, and context and specification managementHands‑on ownership of production backend services/APIs, with practical database and container experienceSystematic AI evaluation using datasets, metrics, baselines, reproducible experiments, and regression detectionDeeper ML foundations, statistical experimentation, and model training or fine‑tuningExperience with runtime isolation and sandboxing for sensitive executionWhat Success Looks LikeFirst 30 days: Understand key workflows and systems, and deliver a prioritized automation backlogFirst 90 days: Ship 3‑5 production automations or integrations with measured impact, and publish AI usage and data‑handling standardsFirst year: Establish a repeatable intake‑to‑deployment process, show clear gains in hours saved and error reduction, and make AI tooling a trusted part of daily operationsHow We Measure ImpactHours saved, cycle‑time reduction, error and rework rates, automation reliability (uptime and failure rate), AI cost per task, and stakeholder satisfaction.BenefitsFully remote work with flexibility to support your work‑life balanceA collaborative environment that empowers you to own your domain and implement best practicesStable income, benefits, adaptable working hours, and opportunities for career advancementFriendly, professional colleagues who are eager to support you and help you growEngaging challenges and opportunities to make a meaningful impact#J-18808-Ljbffr

📌 Applied Ai Engineer - Operations (Valencia)
🏢 Action1
📍 Valencia