# Principal Product Manager – AI Platform at interface.ai

> Onsite · United States · Principal · Product · open. Source: https://alderhq.app/jobs/ashby%3Ainterface-ai%3A7a8fba25-fe2f-4b23-a224-ac48e943725d (read 2026-11-06).

## Facts (observed)

- Company: [interface.ai](https://alderhq.app/companies/interface-ai)
- Location text: San Francisco
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco")
- Posted: 2025-12-16 (326 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/interface-ai/7a8fba25-fe2f-4b23-a224-ac48e943725d
- Skills listed (inferred): LLMs

## Pay and sponsorship

- Posted pay: $250k–$320k per year (from the listing's pay field)
- Market band for similar posted roles (SF Bay Area, n 33): p25 $230k, median $240k, p75 $306k

## Description (the employer's text)

### About Interface.ai

interface.ai is redefining how financial institutions serve their members through agentic AI and conversational AI — and we're doing it in production, at scale, with real outcomes. $30M in Series A funding. Cash-flow positive. A mission that matters: democratizing financial wellness for every American, not just the ones who can afford a private banker.

### The Opportunity

You will own the AI platform that every product at the company depends on. This is not a support function: the platform is the competitive moat. Your decisions directly determine the ceiling of what every other product team can build.

You'll inherit a multi component platform, assess what exists, and define what comes next: what to consolidate, what to invest in, what to sunset. As the senior IC in a pillar of 3-4PMs, you'll set technical direction, mentor, and raise the quality bar, while partnering with engineering leadership to scale the system to millions of end users at startup speed.

### What You'll Own

Agent runtime & orchestration: multi-agent orchestration, memory/context management, tool routing, goal planning, and policy-aligned behavior

Platform contracts: APIs, versioning, deprecation, and migration strategy: you define the boundaries and the lifecycle for all consuming teams

Model lifecycle: selection, evaluation, benchmarking, fine-tuning enablement, and prompt optimization. You define when to prompt-tune vs fine-tune vs switch models.

Inference performance & reliability: latency budgets, caching, batching, quantization, multi-region deployments, fallbacks, and safe rollout patterns (canaries, feature flags, rollback)

Safety & compliance: PII detection/masking, prompt/response safety policies, tenant isolation, SOC2/GDPR readiness, audit logs, and encryption: compliance is a product requirement, not an afterthought

Evaluation & quality: offline golden sets, regression testing, hallucination measurement, task success metrics, and production-to-improvement feedback loops

Voice & multimodal: ASR/TTS integration patterns, WER, interruption handling, turn-taking, and latency budgets for real-time conversational intelligence

Pillar leadership: You set technical direction, mentor, raise the bar, and have input on hiring. You prioritize competing demands from multiple product pillars, define the platform investment thesis, and protect the platform from becoming a feature factory.

### Who You Are

You think in systems, not features. You read a platform outage postmortem and immediately see the product decision that caused it. You've built API contracts that entire product orgs depend on, and you've made the hard call to break one when the platform needed to evolve.

You understand the full AI stack: from model training through inference optimization to production monitoring. You can spec a fine-tuning pipeline, set latency budgets for real-time voice, and debate quantization trade-offs with a staff engineer, all in the same week.

You build your own tools. You use AI to prototype, analyze, and accelerate your work — building agents, writing scripts, creating automated workflows, whatever gets the job done fastest. Not because someone told you to, but because you can't imagine working any other way.

### What You Bring

8+ years in product management, with 3+ years at Staff/Principal level on platform, AI/ML, or infrastructure products

Owned a multi-component platform serving multiple product teams, not just a single product

Deep technical fluency: can read code, review architecture, and debug production issues alongside engineers

Experience with AI/ML platforms: LLM orchestration, model evaluation, fine-tuning, RAG, agentic frameworks, or similar

Experience governing platform contracts and managing how internal teams consume capabilities

Built in enterprise SaaS environments with multi-tenant, compliance, and governance requirements

AI-native workflow: You build with AI daily — creating agents, automating analyses, prototyping with code, building custom workflows. The specific tools don't matter (Cursor, Copilot, Claude, Replit, custom scripts — all count); what matters is that you've moved beyond prompting into building.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Ainterface-ai%3A7a8fba25-fe2f-4b23-a224-ac48e943725d and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.
