VP of Platform Engineering

interface.ai

$180K — $220K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years of engineering experience; 4-6 years in leadership roles at high-growth startups or scale-ups.
  • Experience scaling a platform or infrastructure team through funding transitions.
  • Strong domain knowledge in AI, agentic systems, or conversational AI at production scale.
  • Preferred background as a founder of an AI-native or platform startup.
  • Deep understanding of AI engineering and how LLMs function.
  • Hands-on experience with distributed systems, API design, and cloud architecture; proficient in TypeScript and/or Python.
  • Technical background to participate in code reviews and make architectural decisions; BS/BA in Computer Science required, MS/PhD preferred.

Responsibilities

  • Design and grow the organization for platform domains and build an effective AI/infra team.
  • Oversee the development of the agentic and conversational AI platform, focusing on LLM orchestration and integration.
  • Ensure the velocity and quality of tooling and establish reliability practices across teams.
  • Cultivate an AI-native engineering culture with cutting-edge tools to enhance productivity.
  • Manage engineering and operations excellence, including incident response and reliability targets; collaborate on architecture.

Benefits

  • Opportunity to work at the forefront of AI-native technology.
  • Leadership role that combines technical expertise with strategic team building.
  • Chance to influence and build engineering best practices across the organization.
  • Collaborative environment partnering with senior leadership on architecture and product initiatives.
  • Exposure to cutting-edge tools and technologies used in AI and platform development.
Full Job Description
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.

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