Manager , AI Platform Engineering; Credit Karma

Credit Karma Intuit is looking for a Group Manager of AI Platform Engineering to lead the next generation of AI infrastructure and tooling at one of the most consequential platform organizations in the company. This is a high-impact, high-visibility role at the center of Credit Karma's AI transformation – the AI Platform Engineering group is the foundational force behind the AI Scientists and models that power over 90% of Credit Karma's revenue impact.

As Group Manager, you will have a broad span of control and influence across ML training, feature platforms, and GenAI tooling, with the unique opportunity to shape how AI is built, scaled, and operationalized across the organization. This is a role for a visionary leader who thrives on enabling others to do their best work – someone who sees platform infrastructure as a competitive advantage and is energized by the challenge of turning Credit Karma into a truly…

• Technical Strategy &
  
  Roadmap:
  
  Own the multi-year technical vision for ML training infrastructure, feature platform, and GenAI tooling – translating company AI priorities into a coherent platform strategy that balances near‑term delivery with long‑term scalability. Make build vs. buy vs. open‑source decisions (e.g., Chronon, Ray, Kubeflow) with a clear point of view.
• Platform Reliability & Scale:
  Hold the bar for platform SLAs, reliability, and cost efficiency across training, feature serving, and AI tooling. Drive infrastructure decisions that allow AI Science teams to move faster without accumulating technical debt.
• GenAI Enablement:
  Define and deliver the foundational tooling and infrastructure that enables GenAI development at scale – including evaluation frameworks, agent infrastructure, prompt management, and model lifecycle tooling. Ensure AI teams have production‑grade capabilities, not one‑off solutions.
• Engineering Excellence:
  Set the engineering culture and standards across three teams – code quality, system design, incident response, and operational discipline. Partner with architecture to ensure platform decisions align with broader data and AI infrastructure direction.
• Cross‑functional Partnership:
  Act as the primary platform partner to AI Science, Data Engineering, Engineering and Product – deeply understanding their velocity blockers and translating them into platform investments. Operate as a trusted peer to directors and principal engineers across the organization.
• Stakeholder Influence & Executive Communication:
  Translate complex platform decisions into business impact for executive and non‑technical audiences, while influencing peer directors and senior leaders to align platform investments with company priorities. Build the cross‑functional trust needed to shape roadmap decisions before they're made.
• Team Leadership & Development:
  Build and maintain a high‑performing organization across a team of managers and senior engineers – setting a high bar, developing leadership depth, and fostering a culture of incubation where emerging ideas are explored rigorously and graduated into production‑grade solutions. Own headcount planning, calibration, and org design.

Operational & Financial Accountability:
Own the group's budget, including compute and infrastructure costs. Drive cost attribution models that create transparency and accountability across ML training and serving workloads.

• 10+ years of engineering leadership experience with at least 3–5 years in a manager‑of‑managers or group manager role overseeing multiple teams across ML infrastructure, feature platforms, or AI tooling.
• Deep technical fluency in ML training systems, feature stores (online and offline), and GenAI tooling – to earn the trust of senior engineers and make sound architectural trade‑offs.
• Proven track record of building and scaling high‑performing engineering organizations with a high bar for talent, execution, and engineering excellence.
• Experience partnering closely with a broad range of stakeholders – AI Scientists, product and data engineers, product managers, marketers, and non‑technical business audiences – translating their needs into platform capabilities that accelerate…