VP of Platform Engineering

interface.ai • San Francisco, CA

23h • $400,000 - $500,000

About The Position

Interface.ai is building the AI infrastructure for financial services, bringing agentic AI and conversational AI to credit unions and community banks. The company has approximately $30M in contracted ARR, is cash-flow positive, and is at an inflection point with a proven product and paying customers. The next phase involves scaling the engineering organization. The VP of Platform Engineering will own the platform-engineering half of the organization, focusing on the AI-native core, including the Intelligence domain (agent runtime, knowledge/retrieval, evals, data flywheel), Connectivity (integrations, channels, computer-use/actions-beyond-APIs), Data & Fraud, Assemble (agent-authoring platform), and cross-pillar infrastructure. This role requires deep expertise in agents, LLM orchestration, and the infrastructure for reliable scaling. The leader will build the platform organization and its quality standards, acting as a player-coach who remains hands-on with code and partners with other leaders on architecture and product.

Requirements

• 10+ years engineering experience
• 4–6 years in leadership at high-growth startups / scale-ups
• Scaled a platform / infra team through a funding transition.
• Domain commonality (required): AI / agentic systems, LLM / ML infrastructure, or conversational / voice AI at production scale working on the platform.
• Deep AI engineering fluency — how LLMs work, how to build reliable agentic systems on them, what “agentic AI” means at the infra level.
• Hands-on platform background — distributed systems, API design, cloud architecture, production AI ops.
• Production-scale TypeScript and/or Python.
• Still technical — reviews PRs, makes architecture calls, holds their own with a Staff / Chief Engineer.
• BS/BA in CS required

Nice To Haves

• ex-founder who scaled an AI-native / platform startup (strong preference, not a bar)
• MS/PhD a plus

Responsibilities

• Org design & growth for the platform domains — build and scale the platform / AI / infra team and its standards.
• The agentic & conversational AI platform — LLM orchestration, retrieval systems, evals, and integration / computer-use infrastructure.
• Velocity & quality — the tooling, eval gates, and reliability practices every domain depends on.
• AI-native engineering culture — frontier tools as standard; an engineering harness that makes every engineer 10×.
• Eng/ops excellence — incident response, observability, reliability targets; partner Bruce on architecture and Srinivas on product.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior