Job Description SummaryThis position can be based remotely anywhere in the U.S. (there may be some
restrictions based on legal entity). Please note that this role would not provide
relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the Hiring Manager.
Job DescriptionThe Strategy, Platforms & Transformation team is dedicated to enabling improved decision-making at Novartis by leveraging data and advanced analytics capabilities to generate actionable insights that drive business growth. We collaborate within the US business, bringing insights and challenging ideas to empower smarter, data-driven decision-making. Reporting into ED, AI Strategy and Innovation, this role is crucial in driving AI transformation by bringing the best in AI and tech to unlock opportunities for growth and improve patient outcomes.
The Associate Director, AI Engineer will lead the engineering strategy, design, development, deployment, and ongoing optimization of our agentic AI platform and solutions. This role is responsible for building scalable, secure, and reliable AI-driven systems that transform existing products, processes, and workflows into intelligent, agentic AI experiences. As a key technical leader, the Associate Director will partner closely with product, data, architecture, security, and business teams to define platform capabilities, drive implementation excellence, and operationalize continuous improvement across the AI lifecycle. The ideal candidate brings deep expertise in AI engineering, platform architecture, and production operations, along with a strong track record of translating emerging AI capabilities into practical, high-impact business solutions.
Major Accountabilities - Lead the architecture, design, and engineering delivery of the organization's agentic AI platform and related solutions.
- Drive the transformation of existing products, processes, and workflows into scalable agentic AI-enabled capabilities.
- Oversee end-to-end AI engineering operations, including development, deployment, monitoring, reliability, and continuous improvement.
- Partner with cross-functional stakeholders to define technical roadmaps, platform standards, and solution priorities aligned to business goals.
- Establish engineering best practices for AI system performance, scalability, security, governance, and maintainability.
- Guide the evaluation, integration, and optimization of AI models, orchestration frameworks, and supporting platform components.
- Build, mentor, and lead high-performing engineering teams while fostering innovation, accountability, and technical excellence.
- Identify opportunities to accelerate value delivery through reusable AI services, automation, and operational efficiencies.
Essential Requirements:- Bachelor's degree required and advanced degree preferred, ideally in computer science, engineering, information systems, or a related technical field.
- Six plus years of experience in technology leadership, solution architecture, software engineering, or prototype development, with a strong track record of building and advancing proofs of concept for digital, data driven, or AI enabled solutions.
- Demonstrated experience translating early-stage concepts into functional prototypes or PoCs, including evaluating technical feasibility, defining solution approaches, and working through ambiguty to validate ideas quickly and effectively.
- Strong technical knowledge across modern application development, cloud platforms, data, and AI technologies, with the ability to partner closely with Product, Innovation, Engineering, and Data Science teams to bring concepts to life.
- Experience leading cross functional technical efforts, including guiding developers, coordinating stakeholders, and ensuring PoC work aligns with business goals, user needs, and longer term technical direction.
- Strong problem solving, communication, and execution skills, with the ability to explain technical tradeoffs clearly, manage multiple priorities, and operate effectively in fast paced innovation environments.
The salary for this position is expected to range between $176,400.00 and $327,600.00 annual per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.
EEO Statement:The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.
Accessibility and reasonable accommodationsThe Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to or call and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
Salary Range$176,400.00 - $327,600.00
Skills DesiredArtificial Intelligence (AI), Biostatistics, Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai, Organization Awareness, Pandas (Python), Python (Programming Language), R (Programming Language), Sql (Structured Query Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis
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