WIRB-Copernicus Group

ABOUT WCG:

WCG’s clinical solutions are built on a foundation of best-in-class clinical services companies. We deliver transformational solutions that stimulate growth, foster compliance, and maximize efficiency for those performing clinical trials. WCG is proud to serve individuals on the frontlines of science and medicine, and the organizations striving to develop new products and therapies to improve the quality of human health. It is our role to empower them to accelerate advancement, while ensuring the risks of progress never outweigh the value of human life.

WHY WE LOVE WCG:

At WCG, our employees are our most valuable asset and as with all our assets, we invest in them with an eye toward future success. We provide each eligible employee with a comprehensive set of benefits designed to protect their personal and financial health and to help them make the most of their future.

* Comprehensive Benefits package - Health, Dental, Vision, Life Disability, 401k with match, and flexible spending accounts
* Employee Assistance Programs and additional work/life resources
* Referral Bonuses and Tuition Reimbursement
* Paid time off including holidays, vacation, and sick time
* Opportunities for career development with on-the-job training, certification assistance and continuing education reimbursement

The expected base salary range for this position is $151,200 to $275,000. This salary range may vary based on the candidate's qualifications, experience, skills, education, and geographic location.

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 vendors and distributed/offshore teams
• Familiarity with MLOps and LLMOps practices.
• Experience working in regulated environments (strongly preferred).

SUPERVISORY RESPONSIBILITIES: Overall responsibility of management including direction, coordination, performance, and evaluation of the assigned team and staff. Responsibilities include training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; addressing complaints and resolving problems.

TRAVEL REQUIREMENTS: 10% to 20%