Senior Director, AI Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Implement and operationalize the enterprise AI strategy, ensuring alignment with business priorities and measurable results.

• Lead the design, adoption, and expansion of AI platforms, incorporating ML, GenAI, MLOps, and LLMOps across clinical, regulatory, and operational sectors.

• Balance short-term delivery with long-term platform development by prioritizing AI initiatives.

• Collaborate with executive stakeholders to convert business requirements into scalable AI solutions.

• Develop and scale architectures for AI model creation, deployment, monitoring, and lifecycle management.

• Oversee the implementation and ongoing enhancement of AI platform infrastructure and pipelines.

• Integrate AI platforms within the enterprise data and technology ecosystems.

• Create and uphold Responsible AI frameworks that focus on model validation, bias mitigation, explainability, and auditability.

• Establish AI governance in accordance with GxP, ALCOA+, and data integrity standards.

• Build, manage, and scale globally distributed AI engineering teams.

• Oversee workforce planning, resource allocation, and capability development.

• Collaborate with product, data, compliance, and IT teams.

• Manage strategic vendor relationships and AI-related third-party platforms.

• Perform additional duties as assigned by the supervisor.

• Supervise team management, including direction, coordination, performance assessment, training, task assignments, rewards, discipline, complaint resolution, and problem-solving.

• Travel between 10% to 20% as required.

⛳️ Requirements

• A Bachelor’s degree in Computer Science or a related discipline is required.

• Over 10 years of experience in AI/ML, data engineering, or advanced analytics.

• More than 7 years of leadership experience overseeing global engineering or AI teams.

• Proven experience in building and scaling AI and ML platforms in production settings.

• Demonstrated capability to lead large-scale, cross-functional projects with measurable results.

• Extensive knowledge of ML, NLP, and Generative AI technologies.

• Experience with cloud platforms such as Azure, AWS, or GCP.

• Background in managing vendors and distributed or offshore teams.

• Familiarity with MLOps and LLMOps methodologies.

• Experience in regulated environments is strongly preferred.

• A Master’s degree is preferred but not mandatory.

• Willingness to travel 10% to 20%.

🏝️ Benefits

• Comprehensive benefits package including Health, Dental, Vision, Life Disability, 401k with matching, and flexible spending accounts.

• Access to Employee Assistance Programs and additional work/life resources.

• Referral bonuses and tuition reimbursement opportunities.

• Paid time off encompassing holidays, vacation, and sick leave.

• Career development opportunities with on-the-job training, certification support, and continuing education reimbursement.