Major Responsibilities
- Define and evolve architectural frameworks for the Novartis Generative AI platforms, ensuring they align with business objectives, regulatory standards, and enterprise-grade principles (reusability, scalability, and compliance).
- Lead GenAI solution development through agile methods, iterative prototyping, and continuous improvement. Drive Proof of Concepts (POCs), solution scaling, and stakeholder alignment.
- Architect and implement AI systems that integrate with cloud platforms (AWS, Azure), support LLM lifecycle (LLMOps), and leverage NLP, foundation models, and custom tools / APIs.
- Collaborate with business, IT, data, and security stakeholders to ensure alignment with enterprise data strategy, AI governance, and responsible AI frameworks including transparency, human oversight, and ethical impact assessments.
- Build and manage the GenAI infrastructure and platform operations; establish clear metrics, KPIs, and evaluation frameworks to measure solution impact (business value, process efficiency, and innovation outcomes).
- Foster cross-functional collaboration, knowledge sharing, and adoption of GenAI capabilities across the organization. Provide thought leadership by engaging in AI forums, partner ecosystems, and emerging technology assessments.
- Serve as a trusted advisor and change agent to senior stakeholders driving AI awareness, platform scaling, and integration into enterprise workflows.
Minimum Qualifications
Advanced degree in Computer Science, AI / ML, or related field.20+ years in software architecture and platform engineering, with proven experience in GenAI, NLP, LLMs, and cloud-native systems.Strong programming background (Python, NodeJS, Spark, SQL) with expertise in full-stack and AI / ML tech stacks.Demonstrated success in leading enterprise-scale AI / ML solutions and mentoring high-performing technical teams.Deep understanding of DevSecOps, MLOps / LLMOps practices, agile delivery, and data compliance (privacy, security).Ability to influence and collaborate at executive levels, driving both innovation and operational excellence.Skills Required
Ml, MLops, Ai, Programming Languages, Llm