
Senior Manager, Applied AI
Posted 1 day ago

Posted 1 day ago
This is a fully remote position, open to applicants in North Carolina.
• Oversee a collection of applied AI projects, from defining opportunities and prioritizing initiatives to technical design, development, deployment in production, adoption, and ongoing enhancement.
• Develop technical roadmaps, delivery schedules, success metrics, and resource prioritization across the portfolio.
• Offer technical and delivery guidance in the areas of generative AI, agentic AI, machine learning, and intelligent automation.
• Direct decision-making regarding solution architecture, model and platform selection, data and knowledge architecture, orchestration, evaluation, and production engineering.
• Lead, mentor, and cultivate multidisciplinary technical teams, comprising AI engineers and data scientists.
• Define ownership, accountability, and resource distribution based on business value, complexity, risk, dependencies, and capacity.
• Promote enterprise AI platforms, components, services, APIs, and architectural patterns that are reusable.
• Direct the design and implementation of enterprise-grade AI solutions utilizing large language models, RAG, AI agents, orchestration frameworks, and machine learning.
• Establish AI evaluation and operational practices, including testing, monitoring, observability, performance measurement, reliability engineering, and continuous enhancement.
• Integrate data protection, security, privacy, validation, compliance, and responsible AI practices throughout the AI lifecycle.
• Create technical standards, reference architectures, and development patterns for enterprise AI.
• Collaborate with Product, Digital, Data, Architecture, Security, Quality, Compliance, and business teams.
• Manage delivery accountability across strategic technology partners, vendors, and contingent resources.
• Engage with executive stakeholders effectively.
• Provide technical oversight throughout solution design, engineering, evaluation, testing, deployment, observability, incident response, and lifecycle management.
• Bachelor's degree with 8–10 years of experience in artificial intelligence, machine learning, data science, software engineering, computer science, or a related technology field; or an advanced degree coupled with 7 years of relevant experience.
• Proven experience leading AI or machine learning teams and managing complex technology portfolios within an enterprise setting.
• History of guiding AI solutions from concept and experimentation to production deployment, adoption, and sustained operation at an enterprise scale.
• Deep understanding of generative AI and large language model technologies, including RAG, agentic workflows, tool usage, orchestration, grounding, model selection, prompt and context engineering, and implementation patterns.
• Strong grasp of machine learning, data science, and contemporary AI architecture.
• Familiarity with Azure, AWS, or GCP and modern data, application, and AI architectures.
• Proficient in Python and contemporary AI/ML development frameworks.
• Experience in designing or managing reusable AI platforms, services, APIs, data pipelines, or shared technical capabilities at scale.
• Understanding of AI evaluation, monitoring, model and application performance, data quality, observability, and production reliability.
• Experience operating within data governance, security, privacy, regulatory, and/or responsible AI frameworks.
• Experience managing external technology partners, consultants, or distributed delivery teams.
• Strong product and business acumen.
• Excellent communication and stakeholder management skills.
• Preferred experience in the life sciences or clinical research industry.
• Ability to communicate, receive, and comprehend information and ideas with diverse groups of individuals.
• Capability to maintain an upright and stationary position during standard working hours.
• Proficient in using and learning standard office equipment and technology.
• Ability to perform effectively under pressure while prioritizing and managing multiple projects or tasks.
• Must be legally authorized to work in the United States without requiring sponsorship.
• Must successfully pass a comprehensive background check, including drug screening.
• Variable annual bonus eligibility based on company, team, and/or individual performance results.
• Travel as needed, ranging from 0–20%.
• Remote work opportunities available.
• Relocation assistance is NOT offered.
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