VP of Platform Engineering

interface.ai; San Francisco (CA); On-site; USD 400,000 - 500,000; Full time

Benefits offered by this job

Executive compensation

Job summary

Interface.ai is seeking an AI platform engineer to lead the platform and infra teams, owning the AI-native core including the agent runtime, retrieval/evals, and integrations. You will guide architecture, design scalable systems, and raise the bar for reliability and quality across the organization.

You’ll work hands-on with TypeScript and Python, mentor engineers, and partner with product to ship production-grade AI infrastructure for financial services customers.

Qualifications

• 10+ years in engineering roles or equivalent
• 4–6 years in leadership at high-growth startups / scale‑ups
• Experience building AI/native platform/infra teams
• Hands-on platform background with production AI systems
• BS/BA in CS; MS/PhD a plus

Responsibilities

• Own the platform/infra org design and growth.
• Lead AI-native platform: LLM orchestration, retrieval, evals, integrations.
• Define tooling, gates, and reliability practices.
• Foster AI-native engineering culture and scalable architectures.
• Collaborate with architecture and product leadership on strategy.

Skills

Engineering leadership

AI/agentic systems

LLM infrastructure

Production AI ops

TypeScript / Python

Education

BS/BA in CS

MS/PhD a plus

Tools

Distributed systems

API design

Cloud architecture

Observability/monitoring

Job description

About Interface.ai

Interface.ai is building the AI infrastructure for financial services — bringing agentic AI and conversational AI to the credit unions and community banks that serve everyday Americans. We’re not a lab, we’re not a demo company, and we’re not burning runway on hypotheticals. We are in production, generating real revenue, and on a mission that actually matters: democratizing financial wellness for the millions of people who’ve never had a private banker. A company with $30M in contracted ARR and already cash‑flow positive, we’re at the inflection point — proven product, paying customers, and a team ready to scale. The next chapter is building the engineering organization that can take us there.

THE ROLE

You own the platform‑engineering half of the org — the AI‑native core that everything runs on: the Intelligence domain (agent runtime, knowledge / retrieval, evals, the data flywheel), Connectivity (integrations, channels, computer‑use / actions‑beyond‑APIs), Data & Fraud, Assemble (the agent‑authoring platform), and the cross‑pillar infrastructure. This is the AI‑native specialist seat: the leader must be deep in agents, LLM orchestration, and the infra that makes them reliable at scale, and must build the platform org and its quality bar. A player‑coach who is still in the code, partnering Bruce on architecture.

What You Will Own

• 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 We’re Looking For

• 10+ years engineering; 4–6 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.
• Preferred: ex‑founder who scaled an AI‑native / platform startup (strong preference, not a bar).
• 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; MS/PhD a plus.

Compensation

Compensation Range: $400K – $500K