Director, AI Platforms

SoFi is a next-generation financial services company and national bank using innovative, mobile-first technology to help their millions of members reach their goals. As Director of AI Platforms, you will build and lead a team responsible for AI-enabling platform services and ensure that AI development practices meet regulatory requirements.

Responsibilities:

• Build and run a multi-tenant AI and SDLC platform that provides standardized primitives, including model access, inference serving, prompt and workflow orchestration, feature and retrieval integration, and evaluation tooling
• Establish golden paths for AI development and deployment, including templates, reference architectures, and developer experience workflows that reduce time to first production and increase reuse across teams
• Drive AI-accelerated developer productivity across the engineering organization - embedding AI capabilities into an AI native SDLC to transform how all SoFi engineers plan, code, test, build, deploy, observe, and remediate
• Partner with product and engineering leaders to drive adoption, measure outcomes, and continually refine the platform based on developer feedback and business impact. Teams use your platform because it's the fastest path to production, not because they're required to
• Define and deliver the AI and SDLC platform strategy, roadmap, and operating model, including productization, intake, prioritization, lifecycle management, and deprecation policies
• Lead vendor and ecosystem strategy for AI platform components, including build-versus-buy decisions, model provider evaluation, contracting partnership, and total cost of ownership optimization
• Build governance into the platform, including access controls, data handling controls, auditability, model and prompt change management, and approved usage patterns for regulated workloads. This isn't an approval gate — it's infrastructure that makes the right thing the easy thing
• Own platform reliability and operability, including SLOs, on-call readiness, runbooks, incident response posture, and continuous improvement through post-incident learning
• Implement platform observability for AI systems, including telemetry, tracing, and monitoring for model performance, drift, latency, safety signals, and cost drivers
• Drive automation and standardization across infrastructure provisioning and delivery pipelines, including infrastructure as code, CI/CD patterns, environment management, and policy-as-code guardrails
• Hire, develop, and retain 2-3 high-performing teams of AI and DevEx platform engineers, while setting technical standards and mentoring platform engineering practices across the organization