Technical Platform Operations Lead — Sales AI Applications

NVIDIA is seeking a Technical Platform Operations Lead to join their team and play a crucial role in scaling Sales AI applications and platforms. The successful candidate will collaborate with various teams to ensure platform reliability, security, and continuous improvement.

Job Summary: As a Technical Platform Operations Lead, you will lead end-to-end post-launch operations for Sales AI applications, develop effective processes for incident response and problem management, and analyze service-level indicators and objectives to identify risks and performance degradation.

Key Responsibilities:

• Lead end-to-end post-launch operations for Sales AI applications, including availability, performance, support readiness, releases, upgrades, and lifecycle planning.
• Develop effective processes for incident response, problem management, changes, and issue resolution.
• Analyze service-level indicators and objectives, adoption metrics, dashboards, alerts, and user feedback to identify risks, performance degradation, and usage gaps.
• Collaborate with partner teams to translate operational signals and user needs into prioritized improvements and roadmap inputs.
• Improve adoption and business value through usage analytics, enablement, feedback loops, and user experience enhancements.
• Establish governance practices for security, access controls, compliance, documentation, and platform support.
• Develop automation, observability, and self-service capabilities that simplify operations and reduce repetitive work and recurring incidents.
• Prepare new AI capabilities and releases for production with runbooks, monitoring, rollback plans, support models, and partner enablement.

Requirements:

• 8+ years of experience in technical operations, platform engineering, site reliability engineering, application operations, technical program management, or a related discipline.
• Experience owning production enterprise applications or platforms, including business-critical or customer-facing systems.
• Strong understanding of cloud-native architectures, APIs, distributed systems, data pipelines, integrations, and enterprise software environments.
• Experience applying reliability engineering practices, including service-level indicators and objectives, observability, incident and problem management, root-cause analysis, and service continuity.
• Experience establishing operational governance for security, access controls, releases, compliance, documentation, and audit readiness.
• Ability to use operational metrics, adoption data, and business outcomes to set priorities and communicate platform health to leadership.
• Excellent communication skills and the ability to build alignment across Engineering, Product, Sales, and other partner teams.
• A bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience.

Nice to Have:

• Background with operating generative AI enterprise applications, including AI assistants, retrieval-augmented generation systems, agentic workflows, or Sales productivity tools.
• Experience supporting responsible AI controls, data privacy, access policies, auditability, and the safe use of AI in business functions.
• Experience improving platform economics through cloud or AI cost visibility, usage optimization, capacity planning, or vendor and tool rationalization.
• Experience helping AI or enterprise platforms progress from launch to scaled adoption through effective operating models, self-service capabilities, and sustained reliability improvements.