Artificial Intelligence

• Extend and maintain the CES module
• Define AI integration patterns
• Build wrappers and internal SDKs
• Implement document processing pipelines
• Write integration tests and documentation

AI Development Framework Engineer

• Implement and take part in shaping Visium’s internal AI strategy with leadership, then own it end to end: from direction to a running, measurable operation.
• Design, build and deploy agentic workflows and automations that improve how teams across Visium operate.
• Drive adoption and enablement: build shared resources and reference setups, and design a continuous learning loop that keeps everyone sharp.
• Communicate policies and ways of working clearly, and make people actually want to follow them.
• Measure impact: track adoption and productivity signals, report ROI to leadership, and decide what to keep, kill or change based on the data.
• Make pragmatic build-versus-buy decisions, favouring simple, managed solutions over over-engineering.

AI Operations Lead

• We are looking for a Director of Business Technology & AI Enablement to lead Revizto’s internal IT, workplace technology, enterprise systems, SaaS governance, and AI-enabled business efficiency
• This role is responsible for making our internal technology landscape reliable, scalable, secure, cost-effective, and easy to use
• Lead the evolution of our IT and workplace operations, strengthen our approach to SaaS and vendor management, improve the employee technology experience, and help the company use AI and automation in a practical, governed, and commercially responsible way
• Partner closely with leaders across multiple functions to ensure our systems and tools support the needs of the business today while preparing us for future scale
• Lead and continuously improve Revizto’s IT and digital workplace function in a global, remote-first environment, ensuring best-in-class employee technology experience across the full employee lifecycle, from onboarding and device provisioning to access management, support, changes and offboarding
• Own and improve core IT operations, including helpdesk/service desk structure, ticketing processes, device lifecycle management, endpoint management, access management, software provisioning, documentation, support SLAs, and internal service quality
• Drive a strong internal customer-service mindset within the team, ensuring employees experience the function as helpful, proactive, business-oriented, and solution-focused
• Manage workplace technology and core collaboration tools used broadly across the company, including our company-wide foundations such as Slack, Google Workspace, JumpCloud, Jira, Confluence, and other systems used to support employee productivity, collaboration, access, and knowledge sharing
• Partner with Security to ensure identity, access, device management, software usage, and employee tooling follow appropriate security and compliance standards
• Lead software rationalization efforts by identifying duplicate tools, underused licenses, unnecessary spend, poor adoption, fragmented workflows, and opportunities to consolidate, renegotiate, or improve usage
• Help define clear ownership between business process owners and system owners

Business Technology – AI Enablement Director

• Build a Python-based service to pull data from the HubSpot API
• Develop and maintain ingestion pipelines to move data reliably into BigQuery
• Transform raw API responses into clean, structured tables following our internal data layers
• Connect your datasets to Metabase and build foundational dashboards for internal stakeholders
• Write clear technical guides and data dictionaries for the new integrations

Data Intern – AI

• Serve as EnerSys’ executive leader and single point of accountability for enterprise AI strategy, execution, and outcomes.
• Translate enterprise and business strategies into a clear, multi‑year AI vision and roadmap aligned with growth, productivity, quality, safety, and risk objectives.
• Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications.
• Represent EnerSys externally with strategic AI partners, technology providers, and industry forums.
• Design, implement, and continuously evolve the enterprise AI operating model, including governance forums, funding and intake processes, prioritization methods, and decision rights.
• Chair and run the Executive AI Steering Committee, ensuring disciplined decision making, clear accountability, and execution follow through; set agendas, align key stakeholders, and communicate decisions and actions clearly.
• Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management in partnership with Legal, Cybersecurity, IT Architecture, HR, and Compliance.
• Own AI investment governance, ensuring alignment with capital planning, transformation funding, and enterprise portfolio priorities.
• Own the global AI use case portfolio and prioritization framework, balancing short term value delivery with long term strategic capability building.
• Ensure AI initiatives progress efficiently from ideation to pilot to scaled production—eliminating “pilot only” stagnation.
• Define, track, and report enterprise AI value metrics, including operational efficiency, cost reduction, quality improvement, risk mitigation, revenue enablement, and customer impact.
• Regularly recalibrate the AI roadmap based on realized outcomes, business performance, and evolving priorities.
• Orchestrate cross-functional delivery across IT, data, digital platforms, business units, and external partners—creating shared plans, clear ownership, and fast decisions.
• Resolve enterprise level dependencies and escalations impacting delivery, adoption, or value realization by facilitating trade-off discussions, aligning decision makers, and driving timely, documented outcomes.
• Ensure AI initiatives are integrated with core enterprise platforms (ERP, data environment, digital products) rather than delivered as isolated solutions.
• Build scalable execution playbooks, delivery standards, and reusable components to accelerate adoption across regions and functions.
• Partner with HR and Communications to lead enterprise-wide change management, AI literacy, and workforce enablement.
• Sponsor AI capability building, including training programs, citizen developer models, communities of practice, and leadership education.
• Drive cultural adoption by positioning AI as a core business capability embedded in how work gets done—not as a technology experiment.
• Support workforce transformation planning, including role evolution, ethical considerations, and future skills development.
• Build, lead, and develop a high performing enterprise AI organization with clear roles, succession, and career paths.
• Set performance expectations, accountability, and development plans for direct and indirect reports.
• Foster a strong culture of accountability, collaboration, and execution discipline across the AI ecosystem.

VP, Enterprise AI Enablement

• AI Concept & Strategy: Capture and analyze AI needs from top management and marketing teams. Spot tech trends (GenAI, Agents, etc.) and identify new opportunities for the Swiss Krono Group.
• Rapid Prototyping: Develop agile concepts, run quick feasibility studies (PoCs/MVPs), and deliver ‘quick win’ solutions that move the needle.
• Project Management: Coordinate with external partners, agencies, and tech providers. Independently test and validate new AI tools (Google, OpenAI, Microsoft, etc.).
• Implementation: Lead the rollout of AI solutions, ensuring smooth adoption across the organization.
• Knowledge Sharing: Build internal AI capabilities through demos and best-practice sessions.
• Compliance: Ensure all AI activities meet data protection and internal compliance standards. Administer AI platforms and interfaces for the company.

Manager AI Strategy – Implementation

• **What You’ll Do****Your role can evolve and will depend on our clients’ and internal challenges.
• In general, you will:
• - consult our clients on their path to become a data-driven company, e.g. by assessing the client’s data and machine learning maturity or identifying data-driven use cases and a defining an impactful implementation roadmap
• - interact with our clients to understand their data-related challenges and related tech and business questions they need to answer
• - collaborate with our data scientists, data engineers and IT architects on the implementation of impactful data-based solutions and machine learning use cases
• - consult on the implementation of critical enablers like data governance, model governance, MLOps or analytics centres of excellence
• - interact directly with the head of our Data & AI Consulting practice as part of a small, high-performing team to co-develop the growth strategy and concepts for new data & AI consulting offerings
• - contribute to our business development in preparing and participating in industry conferences, workshops and client sales meetings
• - support the creation of white papers and industry thought leadership on data science & AI-related topics**

Senior Data & AI Consultant – Consulting Lead

• Drive data- and AI-enabled value creation by converting business strategy into prioritized AI initiatives.
• Ensure measurable impact across operations, decision-making, and innovation.
• Build and lead a high-impact AI portfolio, taking ideas from early concepts to scaled solutions that create measurable value.
• Champion responsible and trusted AI by embedding strong governance, ethics, and data standards into everything delivered.
• Elevate data as a strategic asset by improving quality, consistency, and access to enable powerful insights and AI solutions.
• Lead diverse, cross-functional teams to deliver AI initiatives that are practical, scalable, and business-ready.
• Learn from results to continuously refine approaches, scale successes, and amplify business impact.
• Build strong partnerships with business and digital leaders to align priorities and accelerate AI adoption.
• Drive change with confidence by guiding stakeholders through transformation and ensuring responsible adoption of new solutions.
• Inspire, develop, and grow high-performing Data, Analytics, and AI teams aligned behind a shared vision.

Global Data, Analytics and Artificial Intelligence

• Leverage your existing network to source, shape, and close high-value engagements in the DACH region (new logos, not just expansions).
• Translate complex business problems into concrete Data & AI solutions: identify where value can be created, make sure the team is building toward it, and hold the client accountable to realising it.
• Lead and shape complex, tech-enabled transformations — from early problem definition through to scaled delivery — ensuring the right technology choices serve the business outcome, not the other way around.
• Act as the senior point of contact for key clients throughout delivery, ensuring technical execution stays anchored to business value.
• Challenge clients when necessary — on scope, pace, and ambition.
• Work closely with our engineering and data science teams, providing business context, removing blockers, and coaching them.

Managing Director – Data & AI

• Own the end-to-end delivery of AI solutions in the ideate2scale process through stabilization (MVP) until operational handover
• Define, manage, and enforce the transition process, including clear handover criteria and run-readiness gates (setting the basis for continued Dev/Ops)
• Ensure solutions reach the required level of robustness, reliability, maintainability, and operational stability before transfer
• Drive the implementation of monitoring, testing, documentation, support processes, and other prerequisites for productive operation
• Ensure delivered AI solutions meet defined standards for performance, scalability, security, and compliance
• Lead the early-life support phase after deployment and ensure controlled stabilization before handover
• Coordinate business, product, data science, engineering, and run stakeholders to ensure smooth and aligned delivery
• Prepare the run organization through documentation, training, knowledge transfer, and early involvement during the build phase with clear involvement and commitment of the run organization
• Identify delivery risks, technical weaknesses, and operational gaps early and resolve them proactively
• Capture lessons learned from delivery and handover processes and translate them into better standards, methods, and templates

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