
51 - 200 Mitarbeiter
Gegründet 2013
☁️ SaaS
⚡ Produktivität
🏢 Unternehmen
SaaS • Productivity • Enterprise
ActivTrak ist eine führende Plattform für Workforce-Analytik und bietet robuste Lösungen für die Überwachung der Mitarbeiterproduktivität, das Workforce-Management und die Produktivitätsmessung. Mehr als 9. 500 Unternehmen nutzen seine Dienste, um durch aufschlussreiche Produktivitätsberichte, KI-gestütztes Coaching und anpassbare Dashboards die Produktivität und Leistung zu verbessern. Zu den umfassenden Funktionen gehören Zeiterfassung, Planverfolgung, Kapazitätsplanung, Engagement-Erkennung und Technologieoptimierung. ActivTrak engagiert sich für die Transformation der Effizienz und Sicherheit von Arbeitskräften und erleichtert datengesteuerte Entscheidungen für ein verbessertes Leistungs- und Produktivitätsmanagement.
🕒 vor 13 Tagen
🗣️🇺🇸🇬🇧 Englisch erforderlich
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51 - 200 Mitarbeiter
Gegründet 2013
☁️ SaaS
⚡ Produktivität
🏢 Unternehmen
SaaS • Productivity • Enterprise
ActivTrak ist eine führende Plattform für Workforce-Analytik und bietet robuste Lösungen für die Überwachung der Mitarbeiterproduktivität, das Workforce-Management und die Produktivitätsmessung. Mehr als 9. 500 Unternehmen nutzen seine Dienste, um durch aufschlussreiche Produktivitätsberichte, KI-gestütztes Coaching und anpassbare Dashboards die Produktivität und Leistung zu verbessern. Zu den umfassenden Funktionen gehören Zeiterfassung, Planverfolgung, Kapazitätsplanung, Engagement-Erkennung und Technologieoptimierung. ActivTrak engagiert sich für die Transformation der Effizienz und Sicherheit von Arbeitskräften und erleichtert datengesteuerte Entscheidungen für ein verbessertes Leistungs- und Produktivitätsmanagement.
• Define and maintain the AI transformation roadmap, aligned to operational priorities across Revenue, Data, BI, and go-to-market functions • Establish OKRs for AI adoption, productivity impact, and tool ROI, and report progress to the senior leadership • Evaluate, recommend, and govern the AI tool stack, balancing capability, cost, and organizational readiness • Identify the highest-leverage AI use cases across business functions and sequence delivery based on impact and feasibility • Build, prompt, and iterate on AI solutions directly by working in the tools • Design and deploy agentic AI workflows that automate multi-step processes across business functions, moving beyond single-prompt tools to systems that reason, plan and act • Work fluently with Model Context Protocol (MCP) servers to connect AI models to internal systems, data sources, and third-party tools, understanding how to configure, extend, and govern those integrations • Use AI coding tools (including Claude Code and GPT Codex) to accelerate solution development, automate scripts, and build internal tooling without requiring full engineering resources • Partner with the AI Admin on integrations, prompt libraries, and production readiness for new solutions • Lead proof-of-concept work on emerging AI capabilities, stress-testing tools before broader rollout • Manage and develop a small team, setting clear scope, priorities, and success metrics for each role • Create a high-trust, high-output team culture grounded in curiosity, iteration, and business impact • Own the AI governance framework for the organization. Define policies for acceptable use, data handling, model selection and vendor risk across all AI tools and workflows • Establish guardrails for agentic AI systems, ensuring automated workflows have appropriate human-in-the-loop checkpoints, audit trails, and rollback procedures • Partner with Legal, Security, and IT to ensure AI integrations meet data privacy, compliance and information security standards (including SOC 2, GDPR, or customer data handling requirements) • Stay current on the evolving regulatory landscape around AI and proactively surface business implications before they become blockers • Maintain a clear inventory of all AI tools, integrations, and MCP connections in use across the organization, with documented risk ratings and review cadences • Serve as the primary point of contact for all AI needs across ActivTrak — any team, any function, any use case routes through you first • Own and run the AI steering cadence: facilitate cross-functional meetings with business leads, set the agenda, drive decisions and ensure follow-through on commitments • Lead up effectively. You're comfortable presenting roadmaps, risks and recommendations to senior leadership, and you know how to frame tradeoffs in business terms, not technical ones • Influence without authority across peer functions. Build a case and bring people along • Represent the AI Transform function in leadership forums and communicate progress, priorities and risks
• 7 years in operations, RevOps, GTM strategy or technology transformation, with at least 2 years managing people or leading a function • Demonstrated hands-on experience implementing AI solutions in a business context • Fluency with modern AI platforms and the GTM stack: LLMs, no-code/low-code automation, CRM AI features, sequencing tools, enrichment platforms and attribution systems • Working knowledge of agentic AI concepts and architectures. You understand how to design systems where AI models take multi-step actions, not just answer questions • Familiarity with MCP (Model Context Protocol) or equivalent integration patterns for connecting AI to live data sources and internal tooling • Hands-on experience with AI coding tools such as Claude Code, GPT Codex or similar. You are comfortable using these tools to build scripts, automate workflows and accelerate internal development • Demonstrated understanding of AI governance and compliance considerations: acceptable use policies, data privacy, vendor risk, audit trails and human oversight requirements • Active learner who stays current on the fast-moving AI landscape — new model releases, emerging frameworks and evolving best practices — and translates that into actionable guidance for the business • SaaS company experience strongly preferred • Clear, confident communicator who can translate technical concepts for non-technical stakeholders and vice versa • Change management intuition. You understand the hardest part of AI transformation is behavioral, not technical • High ownership orientation. You make calls, iterate and take accountability for outcomes
• Competitive compensation and benefits • Minimal travel. • Limited physical demands.
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