Senior Manager, Applied AI

Stack

Responsibilities

• ▹Lead a portfolio of applied AI initiatives from opportunity definition and prioritization through technical design, development, production deployment, adoption and continuous improvement, with clear roadmaps and delivery plans
• ▹Provide technical and delivery leadership across generative AI, agentic AI, machine learning and intelligent automation, including decisions on architecture, model and platform selection, data and knowledge architecture, orchestration, evaluation and production engineering
• ▹Lead, coach and develop multidisciplinary technical teams, including AI engineers and data scientists
• ▹Drive reusable enterprise AI capabilities (platforms, components, services, APIs and architectural patterns) and prevent duplication
• ▹Lead the design and implementation of enterprise-grade AI solutions using large language models, RAG, AI agents, orchestration frameworks and machine learning
• ▹Establish and improve robust AI evaluation and operational practices: testing, monitoring, observability, performance measurement and reliability engineering
• ▹Embed governance and responsible AI practices throughout the solution lifecycle (data protection, security, privacy, validation, compliance)
• ▹Establish and evolve technical standards, reference architectures and development patterns for enterprise AI
• ▹Partner across Product, Digital, Data, Architecture, Security, Quality, Compliance and business teams, manage delivery accountability across strategic technology partners, vendors and contingent resources, and communicate with executive stakeholders
• ▹Provide technical oversight across the AI development lifecycle: solution design, engineering practices, evaluation, testing, deployment, observability and incident response

Requirements

• ▹Bachelor's degree with 8-10 years of experience in artificial intelligence, machine learning, data science, software engineering, computer science or a related field; or an advanced degree plus 7 years of relevant experience
• ▹Demonstrated experience leading AI or machine learning teams and complex technology portfolios in an enterprise environment, including multiple concurrent initiatives, technical prioritization, architecture decisions, resource allocation and delivery accountability
• ▹Proven experience taking AI solutions from concept and experimentation through production deployment, adoption and ongoing operation at enterprise scale
• ▹Strong understanding of generative AI and LLM technologies, including RAG, agentic workflows, tool use, orchestration, grounding, model selection, prompt and context engineering and production implementation patterns
• ▹Strong understanding of machine learning, data science and modern AI architecture, deep enough to lead and challenge technical design decisions and provide credible technical direction
• ▹Experience with major cloud and AI platforms such as Azure, AWS or GCP, and modern data, application and AI architectures
• ▹Working knowledge of Python and modern AI/ML development frameworks, able to engage deeply in technical designs and review implementations without being the primary hands-on developer
• ▹Experience designing or operating reusable AI platforms, services, APIs, data pipelines or shared technical capabilities at scale, with an understanding of AI evaluation, monitoring, 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, with strong product and business acumen and the ability to connect technology investments to measurable business outcomes
• ▹Excellent communication and stakeholder-management skills, including explaining complex AI concepts, tradeoffs and risks to technical and executive audiences and leading through ambiguity
• ▹Legal authorization to work in the United States without sponsorship; ability to pass a comprehensive background check including a drug screening; as-needed travel (0-20%)

Nice to have

• ▹Life sciences or clinical research industry experience

Soft skills

What we offer

• ▹Estimated annual base salary in North Carolina: USD 130,000-180,000
• ▹Possible variable annual bonus based on company, team and/or individual performance
• ▹Remote work in the USA

About the company

Thermo Fisher Scientific's Clinical Research Group builds purpose-built, CRO-owned digital solutions for drug development. Its AI-enabled solutions support faster study startups, smarter site selection, cleaner data and streamlined regulatory compliance.