Senior Director, AI Engineering (Remote)

WCG delivers transformational solutions that accelerate clinical research and advance human health. We serve the experts, innovators, and pathfinders on the frontlines of science and medicine—empowering them to develop breakthrough therapies while ensuring the risks of progress never outweigh the value of human life. Together, we stimulate growth, maximize efficiency, and shape the future of clinical trials.

Why WCG At WCG, we invest in our people because you are the driving force behind our mission. When you grow, our impact grows. When you thrive, research accelerates. We empower you to build a meaningful career while advancing the work that improves lives.

What We Offer

• Comprehensive health and financial protection – Medical, dental, vision, life and disability insurance, 401(k) with company match, and flexible spending accounts
• Resources that support your whole life – Employee assistance programs and work/life balance tools
• Investment in your growth – Referral bonuses, tuition reimbursement, on-the-job training, certification assistance, and continuing education support
• Time to recharge – Paid holidays, vacation, and sick time
• Pathways forward – Career development opportunities across One WCG

We practice transparency in everything we do, including compensation. The salary range for this position reflects our commitment to fair, competitive pay based on your qualifications, experience, skills, education, and location. Together, we’ll find the right fit for your expertise and our shared mission.

Job Summary The Sr. Director, AI Engineering is responsible for leading the design, development, deployment, and scaling of enterprise AI solutions across the organization. This role drives the implementation and operationalization of AI platforms, including machine learning, generative AI, and intelligent automation capabilities.

This role balances strategic direction with hands-on execution oversight, ensuring AI solutions deliver measurable business value while meeting regulatory, quality, and operational standards.

ESSENTIAL DUTIES/RESPONSIBILITIES: To perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily. The accountabilities listed below are representative of the knowledge, skills, and/or ability required.

• Execute and operationalize the enterprise AI strategy, ensuring alignment to business priorities and measurable outcomes
• Drive design, adoption and growth of AI platforms (ML, GenAI, MLOps, LLMOps) across clinical, regulatory, and operational domains
• Lead prioritization of AI initiatives, balancing short-term delivery and long-term platform evolution
• Partner with executive stakeholders to translate business needs into scalable AI solutions
• Establish and scale enterprise-wide architectures for AI model development, deployment, monitoring, and lifecycle management.
• Drive implementation and continuous improvement of AI platform infrastructure and pipelines
• Ensure AI platforms integrate seamlessly with enterprise data and technology ecosystems
• Establish and enforce Responsible AI frameworks including model validation, bias mitigation, explainability, and auditability
• Establish AI governance aligned with regulatory frameworks (GxP, ALCOA+, data integrity)
• Build, lead, and scale high-performing, globally distributed AI engineering teams
• Drive workforce planning, resource allocation, and capability building in AI engineering
• Collaborate cross-functionally with product, data, compliance, and IT teams.
• Manage strategic vendor relationships and AI-related third-party platforms.
• Other duties as assigned by supervisor. These may, on occasion, be unrelated to the position described here.

Education Requirements

• Bachelor’s degree in Computer Science or related field required; Master’s preferred.

Certifications/License/Registration Requirements

• None

Qualifications/Experience

• 10+ years of experience in AI/ML, data engineering, or advanced analytics.
• 7+ years of leadership experience managing global engineering or AI teams.
• Experience building and scaling AI and ML platforms in production environments.
• Demonstrated ability to lead large-scale, cross-functional initiatives with measurable outcomes
• Deep knowledge of ML, NLP, and Generative AI technologies.
• Experience using cloud platforms such as Azure, AWS, or GCP.
• Experience managing ve…