NVIDIA is looking to solve the problem of improving enterprise value through IT, product, business, and AI collaboration by innovating with modern technology like AI-powered assistants and advanced workplace automation. The company aims to enhance the digital employee experience within the enterprise and define SaaS app strategy from discovery to AI governance.
Requirements
- 5+ years experience implementing AI/ML solutions in business settings; expertise in cloud AI technologies.
- Demonstrated expertise in deploying and operationalizing AI across multiple business and enterprise domains.
- Practical involvement in SaaS application integration, operations using cloud-native technology, and managing the lifecycle of digital workplace devices.
- Strong capability in automation tooling, identity protocols (SCIM, SAML), observability, infrastructure-as-code, and CI/CD.
- Proven governance experience over model lifecycle, data privacy (GDPR/CCPA), and AI ethics; influential communicator across technical and business domains.
- Track record in project management, iterative tech rollouts, executive storytelling with data, and building high-trust teams.
- 12+ overall years enterprise architecture, IT leadership, or large-scale software engineering (including SaaS, digital workplace, and AI/ML systems) with 6+ years Leadership experience.
Responsibilities
- Identify, develop, and implement solutions within enterprise SaaS ecosystems—covering Atlassian, Microsoft 365, Google Workspace, Slack, Perplexity, Datadog, and more—to establish core workflows that boost developer efficiency and improve the overall employee experience.
- Define enterprise AI reference architecture (LLMs, MLOps, vector DBs, RAG patterns, multimodal), aligning Product, IT, and Business roadmaps.
- Own technology standards, guardrails, and domain-specific patterns—balancing innovation with security, privacy, and ethical use.
- Maintain a capability maturity model and staged roadmap for AI, setting clear gate criteria, value metrics, and compliance checkpoints for safe, predictable advancement.
- Lead strategy and delivery for internal business applications, collaboration platforms, and digital workplace technology, ensuring intuitive, secure systems for efficiency and scale.
- Direct multi-functional teams to turn user experience challenges and aging backlogs into production-ready solutions.
- Drive adoption of AI assistants and copilot technologies, and deliver strategic automations through focused engineering squads.
Other
- Lead strategy and drive impactful results for the enterprise.
- Pilot AI-powered technologies and coordinate production deployments, collaborating with Security & Legal on model provenance, IP protection, and risk management.
- Develop and supervise benchmarks, XLAs, and release quarterly AI impact scorecards that translate technical outcomes into important indicators.
- Share results, successes, and findings with executive forums and multi-functional teams, showcasing new opportunities and building momentum.
- Manage budgets, vendor relationships, sourcing, and outcome-based contracts for internal tech and workplace systems.
