Director AI Enablement Lead
Novartis is hiring a Director AI Enablement Lead. It pays €65k-€121k a year and Level rates it ; you can apply on Novartis.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- The posting mentions Bedrock, RAG and fine tuning among its tools and skills.
- Level classes it as an executive role.
- Novartis has 840 other open roles on Level.
- Posted in the last few days.
AI in this role
Salary Range:
€65,200.00 - €121,000.00
Job Description Summary
#LI-HybridLocation: Barcelona, Spain
Job Description Summary
The AI Enablement & Delivery Lead is responsible for defining and executing AI capabilities for the Statistical Compute Environment, related Domino ecosystem and broader Novartis AI landscape.
The role translates business and scientific priorities, Domino product strategy and the Novartis AI landscape into secure, compliant, scalable and production-ready capabilities. It owns delivery from architecture and engineering through adoption and measurable value realization and serves as the technical design and delivery authority across cross-functional teams and vendors.
Working across platform engineering, data science, enterprise AI, security, architecture and business teams, the role integrates the Statistical Compute Platform with the Novartis AI ecosystem, establishes secure and reusable enablement patterns and turns prioritized use cases into production-ready AI solutions.
Job Description
Key Responsibilities
- Define and execute the AI roadmap for the Statistical Compute Environment and related ecosystem, translating Domino product strategy, AQS priorities and the Novartis AI landscape into a prioritized delivery plan and production-ready capabilities.
- Own end-to-end delivery of AI platform capabilities, spanning engineering, security, compliance, production readiness, adoption and measurable business value realization.
- Define the end-to-end GenAI architecture, from cloud model providers such as AWS Bedrock through enterprise LLM gateways to the applications and use cases that consume them.
- Design secure, identity-aware access, including authentication, authorization and traceability, ensuring model usage is secure, auditable and attributable to each user and use case.
- Establish standards and reusable onboarding patterns, defining appropriate guardrails, logging, model access and shared platform services that enable teams to deliver AI use cases quickly and consistently.
- Act as the technical design authority, driving and documenting key architecture decisions across internal teams, platform vendors and cloud providers and taking designs through enterprise architecture, security and compliance reviews.
- Enable production scale, defining requirements for resilience, performance, observability, validation, security and cost management so AI solutions can progress from proof of concept to validated production in a regulated GxP environment.
- Evaluate, onboard and enable AI tools and services, assessing emerging Domino and enterprise AI capabilities and integrating selected services into the QUANTA and broader Novartis AI ecosystems.
- Translate business and scientific requirements into delivered solutions, prioritizing use cases and platform investments, selecting appropriate GenAI and data science techniques and driving implementation and adoption.
- Shape the future AI capability portfolio, identifying high-value opportunities for the quantitative science organization and translating selected innovations into roadmap investments.
Essential Requirements
- Significant experience designing and delivering enterprise AI, GenAI or data science platforms and capabilities at scale.
- Strong expertise in AI platform architecture, including cloud-hosted models, LLM gateways, platform services and production applications.
- Strong knowledge of security, identity and governance, including authentication, authorization, traceability, responsible AI and compliance controls.
- Proven experience taking AI solutions from proof of concept through to scalable, production-ready implementation.
- Practical expertise in GenAI and data science techniques, including prompt and context engineering, Retrieval-Augmented Generation (RAG), fine-tuning, model training and evaluation.
- Experience defining reusable technical standards, shared services and onboarding patterns that enable AI adoption across multiple teams.
- Experience working across complex, cross-functional environments and influencing architecture, engineering, security, data science and business stakeholders.
- Strong communication and stakeholder management skills, with the ability to translate complex technical topics into clear business decisions.
- Fluent English.
Desirable Requirements
- Experience with Domino Data Lab, AWS Bedrock or comparable enterprise AI and machine learning platforms.
- Experience designing AI solutions within pharmaceutical, life sciences or another highly regulated environment.
- Knowledge of GxP, validation and regulated data environments.
- Experience working with technology vendors, cloud providers and strategic platform partners.
Benefits & Rewards
At Novartis, we're committed to reimagining medicine together and rewarding the people who make it happen.
Expected Annual Base Salary Range for the role: 65,200.00 - 121,000.00 EUR Annual
The base salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience, in accordance with the Novartis pay-setting policy, and will be reviewed periodically after joining Novartis.
In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters. Further details will be provided during the application process.
[Include if confirmed as LTI eligible for this level: Long-term equity awards granted at group level may also be part of your package. Further details will be provided during the application process.
The rewards of being part of our team go beyond base pay and incentives. We offer a variety of competitive benefits to help you thrive personally and professionally.
For Spain, these may include a Company Pension Plan, Life and Accidental Insurance, meals/allowance or canteen in the office, and flexible working hours, in line with applicable policies.
Benefits and compensation may vary and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of the compensation package and any relevant collective bargaining agreement details applicable to the role will be communicated separately during the application process.
Commitment to Diversity & Inclusion
Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.
Why Novartis
Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together?
Join our Novartis Network
Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up.
Skills Desired
Budget Management, Business Acumen, Digital Literacy, Operational Excellence (OpEx), Performance Management (PM), Project Management, Risk Management, Service Delivery Management, Stakeholder Management, Strategic Planning, Talent Development, Technology UseHow we rate this
Director AI Enablement Lead at Novartis rates 71 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you think about the risk of an AI system in this kind of role failing silently?
- What's a project where you used Bedrock hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: RAG, Fine-tuning, AI Safety, and Bedrock. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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