AI Tech lead

POSITION SUMMARY

The AI Tech Lead serves as a key technical resource for the ZenAI platform and a critical escalation point for complex platform, integration, and engineering issues. The role requires deep platform expertise and is responsible for feature evaluation, advanced technical consulting, and development of the internal tools on which the team depends. The AI Tech Lead ensures that solutions deployed on ZenAI are optimized for performance, cost efficiency, and model selection; advises power users and technical audiences on advanced platform capabilities; and serves as the technical liaison to vendor engineering and support teams. This role will initially operate as an individual contributor and is expected to evolve into a people-leadership position with one to three direct reports as the team grows. The role also provides complementary coverage across time zones in partnership with the global AI Capabilities & Governance team.

POSITION RESPONSIBILITIES

• Master Data and Capacity Model Ownership: Own the capacity model and related planning master data in SAP IBP. Use the master data dashboard to identify gaps or inaccuracies in production run rates, changeover constraints, material lead times, resource calendars and other planning parameters. Coordinate corrections with the relevant supply planners and master data stewards responsible for maintaining the source data in ECC/S/4HANA.

• Constraint Identification and Alert Generation: Run SAP IBP heuristics and planning algorithms to identify constraints across the supply network. Generate system alerts for capacity bottlenecks, material shortages, safety stock violations, and demand-supply imbalances.

• Scenario Building: Build comparable scenarios with consistent assumptions that enable the Supply Planers in both the Mid-Term and Short-Term to evaluate alternatives. Ensure scenarios are structured, repeatable, and documented so that leadership can compare options on a level playing field.

• Resolution Modelling: Execute resolution modelling in SAP S4 ePPDS and SAP IBP to test proposed solutions before they are committed. Validate feasibility of allocation changes, schedule adjustments, and capacity rebalancing options.

• Digital Twin Development: Drive digital twin development as organizational maturity evolves. Progress the modelling capability through maturity stages: heuristic-based planning, optimizer-driven planning, and ultimately AI/Joule-enabled autonomous planning.

• Data and Parameter Stewardship: Serve as the owner of planning parameters, ensuring that safety stock targets, lot sizes, planning horizons, and aggregation rules are correctly configured and regularly reviewed for accuracy. Ensure issues identified through modelling or business plan validation are escalated and corrected at source where required.

RESOURCES MANAGED

Financial Accountability

None.

Supervision

Initially an individual contributor role. Expected to supervise one to three ZICC-based direct reports (AI Tech Analysts) over time as the team grows.

EDUCATION AND EXPERIENCE

The following education and experience qualifications are required or preferred:

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field required; advanced degree preferred
• 8+ years of professional experience in technical roles such as software engineering, platform engineering, or solution architecture
• 5+ years of hands-on experience with API integrations, enterprise system connections, and automation platforms
• Demonstrated expertise with AI platforms and technologies, including agentic and generative AI
• Experience evaluating, testing, and rolling out new platform features in an enterprise environment
• Proven ability to troubleshoot complex technical issues across multiple systems
• Experience building internal tooling, dashboards, and automation solutions
• Prior people leadership or team lead experience preferred
• Experience in the pharmaceutical, life sciences, or regulated industry preferred

TECHNICAL SKILLS REQUIREMENTS

The following technical skills are required or preferred:

• Deep expertise with enterprise AI platforms and technologies, including agents, workflows, skills, integrations, and agentic AI; experience with Langdock, OpenAI, or similar platforms preferred.
• Experience with MCP (Model Context Protocol) services and MCP gateways; experience with REST APIs, w…