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.
Compensation
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.
Responsibilities
Define and execute the AI roadmap for the Statistical Compute Environment and related ecosystem
Own end-to-end delivery of AI platform capabilities
Define the end-to-end GenAI architecture
Design secure, identity-aware access
Establish standards and reusable onboarding patterns
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.
Compensation
Expected Annual Base Salary Range for the role: 65,200.00 - 121,000.00 EUR Annual
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.
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.
Individual-contributor leadership role to define and drive the product strategy for enterprise non-human identity (NHI) and agentic identity across consumer, workforce and shared identity platform use cases.
Locations (3)
United States
Minneapolis, Minnesota, United States
Washington, D.C., District of Columbia, United States
Responsibilities
Own the product vision, strategy and multi-year roadmap for enterprise non-human, machine, workload and agentic identity capabilities across consumer, workforce and shared platform use cases
Define the problems to solve, target outcomes, sequencing, adoption model and investment choices, while keeping the product direction durable through organizational change
Identify what should be common across the enterprise and where consumer, workforce or business-domain differences require distinct solutions
As an AI Product Owner, you will serve as the strategic driver behind SCAN’s agentic AI platform, translating vision into actionable outcomes. You’ll own the requirements, validation strategy, and delivery of value, ensuring that robust, scalable, and innovative AI solutions meet evolving business needs.
Compensation
Base Salary Range: $106,200 to $182,983 annually
Responsibilities
Gather, refine, and prioritize technical and business requirements for platform features and agents
Translate business needs and organizational patterns into clear, actionable specifications for engineering teams
Make trade‑off decisions regarding implementation (e.g. AI vs. non‑AI) and maintain a prioritized feature backlog
Use market headwind/tailwind to scope and envision AI platform features, expanding from workflows, scheduling, triggers, and integration points
Strategize and roadmap development of APIs, Model Context Protocol (MCP), and knowledge/data management systems
Requirements
Bachelor's Degree or equivalent experience in Computer Science, Engineering, or a related field
Nice to have: SAFe Agile Certification
Nice to have: Azure AI Engineer Associate
Nice to have: Azure Data Scientist Associate
Nice to have: certifications in data engineering, machine learning, or AI solution architecture
Design and deploy large-scale HPC and GPU infrastructure and architect scalable AI solutions on OCI, serving as a technical advisor for enterprise customers.
Responsibilities
Design and deploy large-scale HPC and GPU infrastructure on Oracle Cloud Infrastructure (OCI)
Architect scalable AI and accelerated computing solutions using Infrastructure as Code (Terraform, Ansible) and Kubernetes.
Develop automated deployment frameworks for cluster provisioning, software installation, and lifecycle management.
Partner with enterprise customers to design solutions that meet AI, machine learning, and high-performance computing requirements.
Design and support Large Language Model (LLM), Agentic AI, and AI platform deployments from proof-of-concept through production.
Requirements
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical discipline
Nice to have: Experience with Oracle Cloud Infrastructure (OCI)
Nice to have: Experience with large GPU clusters based on Kubernetes and/or Slurm
Nice to have: Experience supporting AI startups, research organisations, or enterprise AI programmes
Nice to have: Oracle Cloud certifications or equivalent cloud certifications (AWS, Azure, or Google Cloud)
Lead the Prism team as a people manager. Prism is SoFi’s internal AI platform for knowledge work.
Locations (2)
San Francisco, California, United States
Seattle, Washington, United States
Compensation
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
Responsibilities
Build and scale Prism: Lead the engineering team responsible for developing SoFi's internal AI productivity platform.
Manage and develop talent: Manage incoming IC3 engineers, providing coaching, performance management, and career development.
Execute the technical roadmap: Help define and deliver on the internal AI-platform roadmap, adapting to shifting priorities while ensuring short-term operational targets are met.
Build foundational AI infrastructure: Oversee the development of tools that enable SoFi engineers to work more productively, including custom harness wrappers, auto-routing capabilities, and programmatic evaluations.
Drive alignment across authentication, authorization, security, architecture, AI platform, consumer product, workforce identity and participating lines of business
Convert shared architecture and policy dependencies into explicit product decisions, roadmaps, requirements and accountable owners
Partner with stakeholders: Work directly with internal developer customers and cross-functional engineering teams to distill complex requirements, obtain buy-in, and drive platform adoption.
Requirements
Bachelor's Degree + 4+ Years of Experience
Master’s Degree + 3+ Years of Experience in software engineering, computer science, or a related field
Nice to have: Experience in fintech or within another highly regulated industry environment
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