Senior Director, AI Engineering and Delivery

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare with leading businesses and products in diagnostics medical devices nutritionals and branded generic medicines. Our 115000 colleagues serve people in more than 160 countries.

The organization is making a strategic investment in AI and Generative AI and is creating a senior leadership role to architect scale and operationalize AI as a core platform capability.

This is a rare opportunity for a deeply technical platform-oriented AI leader to shape how AI is engineered governed and consumed across a complex regulated multi business environmentmoving the organization from pockets of innovation to enterprise-wide AI at scale.

The Head of AI Engineering and Delivery will lead the design build and evolution of enterprise AI and Generative AI teams and platforms for a global organization operating in life science medical technology-driven markets. This leader will bring deep technical credibility across software engineering data engineering AI / machine learning and cloud-native architecture combined with a proven ability to build and lead technical teams operating within a highly regulated environment.

The role is responsible for creating reusable secure and scalable AI capabilities that empower product teams business units and operations to rapidly develop and deploy AI-driven solutions. The role will serve as a senior engineering and architecture authority for AI platforms ensuring consistency governance and speed while enabling innovation across the enterprise.

• Build and lead a new AI Engineering & Delivery organization operating across three layers: Platform Delivery and Enablement
• Establish AI and GenAI as core enterprise platforms not bespoke solutions.
• Enable self-service AI capabilities for product engineering and analytics teams.
• Balance innovation velocity with regulatory compliance and operational resilience.
• Drive measurable business outcomes across customer experience risk operations and productivity.
• Build and lead delivery teams to execute on the strategic mandate developing a future focused delivery operating model.

What Youll Work On

Define & Execute AI Platform Strategy

• Set and drive a unified cross-business-unit AI platform strategy ensuring seamless integration across products services and geographies
• Establish AI and GenAI as core enterprise platforms not one-off solutions
• Champion API-first platform-based architectures that accelerate time-to-market while reducing total cost of ownership
• Drive alignment across architecture proposals to maximize reuse standardization and leverage of shared AI and software services
• Plan and implement overall AI strategy; develop enterprise priorities and facilitate business and IT governance related to information design and business insight delivery

Build & Scale AI Engineering Delivery

• Build and lead the AI Engineering & Delivery organization spanning Platform Delivery and Enablement
• Establish best-in-class delivery practices for AI Software and Data Engineering including discovery build test automation validation observability and reliability
• Own the end-to-end AI and data engineering ecosystem: cloud-native platforms AI/ML systems connectivity and secure data pipelines
• Drive end-to-end observability across data pipelines model inference tool execution and agent outcomes with clear SLIs/SLOs for quality latency reliability and cost
• Standardize ML and agent development workflows to reduce time-to-production and eliminate bespoke infrastructure across teams

Enable GenAI & Emerging Technology at Scale

• Partner with business unit leaders to incubate industrialize and scale AI and Generative AI capabilities including:

• Machine learning and advanced analytics
• GenAI copilots autonomous agents and intelligent assistants
• Agent lifecycle management: CI/CD model registries lineage and access control
• RAG prompt orchestration evaluation and guardrails
• Process optimization and reengineering
• Modern data science platforms and development frameworks

• Make agent evaluation and experimentation default platform capabilities offline evaluation pre-deployment quality gates and continuous post-deployment monitoring
• Translate innovation into production-grade governed AI systems that deliver measurable business value

Governance Risk & Responsible AI

• Embed Responsible AI principles into platform design and engineering practices from the start
• Partner with Risk Compliance Legal and Security to ensure model governance lifecycle controls and regulatory compliance across jurisdictions
• Ensure AI-enabled systems meet enterprise standards for security performance resilience and regulatory compliance including FDA SOX MoH and regulations applicable to pharmaceutical food and medical device industries
• Implement and maintain compliance controls and policies applicable to pharmaceutical food and medical device industries
• Act as a senior voice in AI risk and governance forums across the enterprise

Organizational Leadership & Influence

• Recruit develop and retain world-class technical talent; foster a culture of excellence accountability and continuous learning
• Provide clear leadership mentoring and guidance to senior leaders principal engineers and architects across the enterprise
• Act as a connective force across Technology Product Operations Cybersecurity Compliance and Commercial teams
• Serve as a trusted advisor to executive leadership on technology strategy investment decisions and transformation roadmaps
• Work in partnership with business and IT to govern total cost of investment for existing reporting environments with a focus on standardization and consolidation

Success Profile (First 1224 Months)

A unified AI and GenAI platform is live and broadly adopted across the enterprise. Product and business teams can rapidly build AI capabilities using standardized services. AI risk governance and compliance are embedded by design not retrofitted. AI engineering is viewed as a strategic technology capability enabling speed safety and scale delivering measurable outcomes.

Required Qualifications

• Bachelors degree required (Business Computer Science Engineering Data/Analytics or related)
• 15 years of experience in software engineering and large-scale platform development.
• Demonstrated success building and scaling enterprise platforms in financial services fintech or global technology firms.
• Strong expertise in:
• Distributed systems and modern software architecture
• Cloud platforms (AWS Azure GCP) in regulated environments
• API microservices and event-driven architectures
• Platform reliability observability and cost management
• Proven track record delivering production AI and ML systems in real-world regulated contexts.
• Hands-on experience with: Machine learning lifecycle management (MLOps); Model monitoring retraining and performance management; Generative AI and foundation models (LLMs); RAG prompt orchestration evaluation and guardrails; Experience operationalizing AI with risk controls explainability and governance.
• Experience leading large globally distributed engineering teams.
• Strong stakeholder management skills across Technology Risk Compliance and Business leadership.
• Demonstrated ability to shift organizations toward platform-led reuse-driven delivery models.
• Track record of aligning AI platform investments to revenue growth cost efficiency risk reduction or customer outcomes.
• Proven leader of large global multidisciplinary teams
• Platform mindset with a bias toward reuse leverage and scale
• Clear communicator who can translate complexity into executive-level decisions.
• Comfortable operating in highly regulated high-stakes environments.

The base pay for this position is

$190000.00 $380000.00

In specific locations the pay range may vary from the range posted.

IT Business Relationship Management

BTS Business Technology Services

United States > Abbott Park : AP06C

United States > Chicago : Willis Tower Building 233 S Wacker Dr.

Standard

Yes 15 % of the Time

Not Applicable

Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)

Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.

EEO is the Law link - English: EEO is the Law link - Espanol: Experience:

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