Summary Of The Job
We are seeking an experienced
Summary Of The Job
We are seeking an experienced AI Platform Lead to drive the design, development, and operation of our enterprise AI Platform, enabling scalable, secure, and impactful AI solutions across Holcim.
The AI Platform Lead will be responsible for the platform’s strategic roadmap, technical architecture, operational excellence, and stakeholder engagement, ensuring it supports diverse AI use cases—Assistants, Agents, automation, and advanced analytics—across manufacturing, logistics, customer service, procurement, finance and sales and other enabling functions.
You will lead a cross-functional team of engineers, architects, and AI specialists, working closely with business units to ensure the platform’s capabilities meet current and future enterprise demands.
Main Activities / Responsibilities
Strategic Leadership
- Own the AI Platform vision and roadmap, ensuring alignment with Holcim’s digital and AI transformation goals.
- Translate strategic business objectives into AI platform capabilities and integration strategies.
- Maintain a technology radar for emerging AI and ML technologies, tools, and frameworks.
Platform Architecture & Development
- Oversee the architecture and evolution of the AI Platform, including:
- Operational Backbone integration (ERP, Logistics, Manufacturing).
- Customer Identity & Access Management.
- Integration Layer for APIs, SDKs, and multi-LLM routing.
- Define and enforce architecture principles for scalability, performance, and security.
- Drive adoption of AI Gateways, Low-Code/No-Code AI tools, RAG, and orchestration frameworks.
Operational Excellence
- Ensure platform reliability, observability, and governance, including:
- Security & compliance (PII protection, GDPR).
- Observability (logging, tracing, performance monitoring).
- Cost management and optimization for AI workloads.
- Establish and maintain SLAs and operational KPIs.
Stakeholder & Team Management
- Collaborate with business stakeholders to prioritize and deliver AI use cases.
- Partner with Data Science, Engineering, and IT teams to ensure seamless integration with enterprise systems.
- Lead and mentor a multi-disciplinary team of platform engineers, AI specialists, and integration experts.
- Engage with vendors and partners for AI technology acquisition and integration.
JOB DIMENSIONS
List of direct reports:
- Up to 7 Direct Reports, and around 15 externals
Key interfaces, stakeholders and relationships:
- Internal:
- GDS: product manager, Technical product manager, regional Digital Center management, GDS senior leadership team
- Group functions: Marketing & Innovation, Finance, Sustainability
- Country commercial and operations leaders
- External : 3rd party vendors
Profile Required
- Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or related field.
- Experience:
- 5+ years in AI, ML, or data platform leadership roles.
- Proven experience building and managing enterprise AI/ML platforms.
- Strong background in AI architecture, API integration, and MLOps.
- Experience with multi-LLM orchestration, AI gateways, and vector databases.
- Technical Expertise:
- Cloud-native platforms (AWS, or GCP).
- AI/ML frameworks (LangChain, LlamaIndex, Hugging Face, etc.).
- Low-code/no-code AI tools (Flowise, N8N, Dify, etc.).
- API management & integration platforms.
- Security and compliance in AI systems.
- Leadership: Ability to lead cross-functional teams and drive transformation in a complex enterprise.
- Communication: Excellent stakeholder management, strategic storytelling, and technical documentation skills
Language skills:
- Excellent English (written & spoken) - other languages are a plus
Preferred Qualifications
- Experience in construction materials, manufacturing, or logistics sectors it’s a plus.
- Familiarity with Holcim architecture principles it’s a plus.
- Prior experience with voice AI, AI assistants, and AI agents in enterprise environments.
Success Measures
- Adoption & Value: Number and impact of AI-powered solutions deployed via the platform.
- Platform Performance: Uptime, latency, cost efficiency, and scalability metrics.
- Business Impact: Tangible improvement in productivity, customer experience, and decision-making.
- Innovation Pace: Ability to integrate emerging AI technologies without disrupting stability.
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