Role Description As an AI Operations Manager (all genders), you drive how envelio adopts and uses AI internally as a company - discovering high-value AI use cases across departments and shaping them into a coherent landscape that teams actually use, rather than a patchwork of individual experiments. Above all, you are the enabler and connector for AI adoption across envelio. The heart of this role is working hand in hand with every department: - Discovering concrete AI use cases - Understanding what value AI can bring to each team's value streams - Turning those opportunities into real adoption on the ground This is a senior individual contributor role with company-wide reach. You don't manage people, but you shape decisions and patterns that touch every function at envelio. Who You Work With - Department leads across envelio - your primary stakeholders and the source of most use cases - AI champions in every department - embedded counterparts who scout use cases, pilot patterns, and drive adoption inside their teams - AI Platform Engineers - the role that owns the technical direction, platform, and architecture - Engineering teams building or using internal AI - you bring use cases to them and collaborate closely - Governance, security, and executive leadership - partners on direction, policy, and decisions How You Make an Impact - Act as the enabler and connector for AI adoption across envelio - Build a clear picture of where AI can create value across how envelio works internally - Surface and champion the use cases teams pursue and help define what success looks like - Translate department needs into clear requirements for AI tooling and AI-enabled SaaS - Bring the use-case and value perspective into envelio's strategic AI questions - Partner with governance to translate policy into patterns teams can follow - Bring deep technical credibility to every department Qualifications - Strong software engineering background at senior level or above - Strong conceptual fluency across the main AI building blocks (LLMs, vision, multimodal, classical ML) - Track record of leading cross-functional AI or architectural efforts across multiple teams - Pragmatic about build vs. buy, and comfortable with governance, compliance, and risk - Strong communicator with audiences outside engineering - Fluent in English; German is a plus Benefits - Join us fully remote or at our lovely office in Cologne in a hybrid working mode - Option for remote work from abroad (up to three months per year from anywhere in the EU or the USA) - State-of-the-art technology and modern tech stack - Excellent hardware equipment (16-inch MacBooks, 2 screens at the office) - 30 holidays + 3 corporate holidays - Support for your health through sports membership cooperations - Flexible use of a monthly mobility budget (e.g. Jobrad, public transport) - Time and resources for individual growth - envelio pension plan - Professional mental wellbeing support through our partner nilo for you and your family - Regular tech and growth talks for internal knowledge sharing - Regular company and team events

• Analyze funnel performance, conversion trends, pipeline movement, campaign effectiveness, and lead flow. • Use data & reports from various tools such as CRM & Marketing Automation Platform, spreadsheets, BI tools, and structured analysis to identify gaps, inefficiencies, risks, and optimization opportunities. • Support forecasting, pipeline initiatives, attribution, pipeline inspection, revenue reporting, risk, retention, expansion, and business health initiatives through strong operational and systems-based thinking. • Define how these signals should translate into action. • Partner with Sales, Marketing, Customer Success, and RevOps stakeholders to determine which workflows should remain human-led, which should be AI-assisted, and which are appropriate for automation. • Partner closely with Sales Enablement to ensure AI is incorporated into training Sales. • Translate reporting and analytical findings into workflow improvements, automation opportunities, and data requirements. • Automate repeatable revenue operations tasks such as lead routing, enrichment, follow-up prompts, campaign triggers, pipeline hygiene, task creation, operational alerts, and data quality checks. • Build internal copilots, agents, workflow assistants, and AI-assisted tools that help Sales and Marketing teams act more quickly, consistently, and effectively by listening for signals, recommend actions, trigger workflows, support engagement, and assisting with pipeline movement. • Test, build, and scale the business logic, signal models, operating rules, & success criteria for AI-enabled revenue workflows that help summarize account activity, identify next-best actions, prioritize leads or opportunities, surface pipeline risks, and improve follow-up consistency. • Establish feedback loops to improve workflow logic, agent behavior, recommendation quality, and business impact over time. • Partner with Technology on LLM usage, agent patterns, integration approaches, data boundaries, monitoring, and production deployment where workflows require cross-system or enterprise-grade implementation. • Work with Technology, Data, Security, Sales, Marketing, and RevOps stakeholders to align automation efforts with company standards for data access, privacy, security, auditability, and system reliability. • Use existing data infrastructure where available and identify data gaps that limit revenue visibility, automation, or AI-driven decisioning. • Partner with technical teams on APIs, integrations, orchestration patterns, monitoring, and scalable deployment where workflows cross system boundaries. • Continuously test, iterate, and improve workflow logic, messaging, routing, prioritization, automation rules, and AI-assisted recommendations. • Build practical reporting that shows whether automation and AI-assisted workflows are improving revenue operations performance. • Use findings from pilots and production workflows to refine future automation priorities and inform the broader revenue automation roadmap.

• Own Workday architecture & configuration • Own the business process framework inside Workday — how approvals route, how tasks trigger, how workflows sequence across the employee lifecycle • Configure and maintain security roles so the right people have access to the right data • Build and maintain custom reports and calculated fields that feed compensation decisions, headcount tracking, and org management • Design and maintain integrations between Workday and our broader People tech stack — payroll, Pulley, and Ashby — so data flows automatically without manual reconciliation • Audit and continuously improve system configuration as the org grows and business needs change • Serve as the internal Workday expert — the person who knows what the system can do and pushes us to actually use it • Identify manual, repetitive workflows across the People function and build automations that eliminate them • Evaluate and implement AI tools relevant to People Operations, compensation, and systems administration • Partner with the Total Rewards & Infrastructure Lead to build and execute a People AI roadmap • Stay close to what Workday is releasing natively on AI and automation and bring those capabilities in-house • Build and maintain the data infrastructure that powers compensation decisions — salary bands, job architecture, and leveling frameworks • Support the annual compensation review cycle from a systems and data perspective • Maintain equity administration in Pulley and ensure clean data across grant history, vesting schedules, and terminated employee records • Partner with Total Rewards & Infrastructure Lead on compensation modeling and scenario analysis as we scale

• Embed with enterprise clients to design, build and operationalize agentic AI solutions • Build production outcomes for clients and integrate agentic systems with enterprise platforms • Lead technical discovery, scope agentic AI use cases, and translate business problems into engineering deliverables • Design target architectures that fit the client's environment, regulatory posture and platform preferences • Write production-grade code and work inside the client's source control, CI/CD, and deployment infrastructure • Build and tune retrieval pipelines and implement enterprise-safe agent tool execution • Build evaluation suites that catch hallucinations, regressions, grounding gaps and quality drift • Stay engaged through cutover and the first production iteration cycle • Act as an escalation backup to the support team after handover • Build trusted advisor relationships with client engineering, data, security and business stakeholders