Executive Director, AI Enterprise Process & Innovation

AstraZeneca • Gaithersburg, MD

1d

About The Position

We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real. Purpose Drive end-to-end process transformation across the value chain - spanning Operations, Manufacturing, Supply Chain, and Commercial - by embedding AI at the point of work to improve quality, service, speed, cost, and patient impact. Shift the enterprise from function-centric workflows to decision-centric operating models that eliminate bottlenecks and reduce manual handoffs, with a particular focus on high-value decisions in manufacturing execution, quality, planning, procurement, field engagement, and revenue growth.

Requirements

• Proven leadership in redesigning end-to-end processes across Operations, Supply Chain, Manufacturing, and Commercial environments, transitioning from function-optimized workflows to AI-enabled, decision-focused operating models.
• Demonstrated ability to identify and remove bottlenecks, manual handoffs, and slow decision points - and to build intelligence into workflows rather than layering tools.
• Strong integrator who connects business, technology, data, and change capabilities to deliver enterprise innovation - incubating and expanding AI use cases in R&D, Manufacturing/Quality, Supply Chain, Commercial, Medical, Legal, Finance, and Procurement - with repeatable methods to progress from pilot to scaled capability.
• Internal consultancy and value realization experience with executive stakeholders in Operations, Manufacturing, and Commercial: shaping problem statements; building value cases tied to OEE, yield, cycle time, scrap/rework, forecast accuracy, service levels, and revenue growth; partnering with Finance to define metrics, track benefits and ROI, and secure sustained impact; advising where AI changes operating leverage.
• AI operating model and governance: Experience partnering with Enterprise AI, Data, IT, Risk, Quality, Legal/Compliance, and GBS to deploy responsible AI in regulated environments—GxP manufacturing and quality, as well as compliant Commercial use cases - balancing speed with safety and trust.
• Change leadership and capability building in operational and commercial contexts: driving adoption with new ways of working and decision accountability across plants, supply chain functions, and field forces; educating senior leaders; building talent and communities of practice in process innovation, AI product thinking, and architectural planning; thoughtful succession planning.
• Delivery and scale: Track record orchestrating cross-functional squads to embed AI into day-to-day operations (e.g., predictive maintenance, batch release prioritization, quality trending and signal detection, IBP/S&OP decision support, next-best engagement, omnichannel optimization) and communicating benefits across cost, quality, service, and growth dimensions to evidence ROI.
• Executive-level advisory experience translating ambiguous operational and commercial challenges into clear value cases and operating leverage, with a consistent record of delivering line-of-business impact.
• Expertise in decision-centric operating models, process engineering, and systems design; familiarity with Lean, Six Sigma, TPM, and digital/advanced manufacturing methods (e.g., CPV, eBR, PAT) as well as Commercial excellence practices (e.g., segmentation, targeting, incentive comp, payer/access strategy).
• Proficiency in AI product thinking, ML engineering and MLOps, large language models and orchestration, and data platform integration—applied to use cases such as maintenance and yield optimization, deviation/root cause acceleration, quality analytics, demand forecasting, supply planning, and omnichannel/customer engagement.
• Experience establishing and operating governance for secure, responsible AI in regulated manufacturing and compliant Commercial settings, in partnership with risk, quality, and legal/compliance.
• Strong storytelling and education skills to engage senior operations and commercial leaders and mobilize multidisciplinary teams; demonstrated succession planning and talent development.
• Ability to orchestrate cross-functional squads and deliver from idea to pilot to scaled capability with measurable improvements in OEE, cycle time, cost-to-serve, service levels, and revenue growth.

Nice To Haves

• Advanced degree preferred.

Responsibilities

• Redesign critical end-to-end processes with a value-chain lens. Focus on decision-centric models that integrate AI into daily work across Manufacturing (e.g., shop-floor decision support, batch release, deviation triage), Operations/Supply Chain (e.g., demand/supply planning, inventory optimization, logistics), and Commercial (e.g., next-best action, customer engagement, pricing/contracting).
• Remove structural bottlenecks and reduce decision latency to deliver measurable business outcomes.
• Act as a cross-functional integrator to incubate and scale AI-enabled use cases across Operations, Manufacturing, Quality, Supply Chain, Commercial, Medical, Legal, Finance, and Procurement.
• Establish repeatable pathways to move from pilot to scaled enterprise capabilities with proven impact on service levels, cycle time, yield, and revenue.
• Partner with senior leaders in Operations, Manufacturing, and Commercial to frame problem statements, quantify benefits, and align AI solutions to outcomes such as OEE, throughput, COGS, right-first-time, forecast accuracy, customer engagement effectiveness, and growth.
• Collaborate with Finance to define value metrics, track benefits realization and ROI, and ensure sustained impact.
• Advise where AI shifts operating leverage versus where traditional optimization suffices.
• Collaborate with Enterprise AI, Data, IT, Risk, Quality, Legal/Compliance, and GBS to ensure solutions are scalable, secure, compliant, and ethical - fit for regulated manufacturing and GxP environments, data privacy in Commercial, and enterprise-grade risk controls.
• Codify pragmatic governance that accelerates delivery without compromising safety or trust.
• Lead adoption through new ways of working, role redesign, and clear decision rights - across plant operations, global supply chain, and field/commercial teams.
• Build enterprise understanding of AI’s role in process transformation through executive storytelling and hands-on engagement on the shop floor and with go-to-market teams.
• Develop talent and communities of practice in process innovation, AI product thinking, and systems design; plan for succession.
• Lead or coordinate complex, high-value, AI-enabled improvement initiatives from idea to pilot to scaled capability.
• Orchestrate cross-functional squads to remove blockers and embed AI into routine operations (e.g., eBR/eDHR enhancements, CPV analytics, quality signal detection, S&OP/IBP decision support, territory/customer orchestration).
• Socialize strategic outcomes demonstrating cost, quality, service, and financial improvements.

Benefits

• Short-term incentive bonus opportunity
• Equity-based long-term incentive program (salaried roles)
• Retirement contribution (hourly roles)
• Commission payment eligibility (sales roles)
• Qualified retirement program [401(k) plan]
• Paid vacation and holidays
• Paid leaves
• Health benefits including medical, prescription drug, dental, and vision coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Number of Employees: 5,001-10,000 employees