---
title: 'Founding Customer Operations Lead at Specter'
canonical: 'https://feeny.ai/job/founding-customer-operations-lead-specter-san-francisco-4e0jb5pg08bh'
type: 'job'
last_seen: '2026-10-19'
---

# Founding Customer Operations Lead at Specter

- **Company:** Specter
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-06
- **Last confirmed live:** 2026-10-19
- **Apply:** https://jobs.ashbyhq.com/specter/86aa5df0-041c-45ae-8479-0fad48b15bcc

## Job description

Company Background Specter's mission is to help automate the physical world.

Today, we build video sensors with state-of-the-art AI agents that answer any question, anywhere in their environments. Our systems can automatically detect and reason about any physical activity captured on camera, from security incidents (e.g. perimeter intrusion, theft, LPR), to safety monitoring (e.g. PPE detection, injured people), to operational efficiency (e.g. material tracking, congestion monitoring). We offer both long range wireless (1km range) and wired sensor variants to suit any deployment.

Our co-founders Xerxes and Philip are passionate about empowering our partners in the fast approaching world of physical AI and robotics. We are a small, fast growing team who hail from Anduril, Tesla, Uber, and the U.S. Special Forces.

## The Role

Customer Operations is accountable for keeping Specter working for every customer. When we or a customer identify an issue, proactively communicate, triage, and resolve it. One person owns the problem from the first report to resolution. Success is measured by reliability: we catch issues before our customers do and fix them fast.

As our Founding Customer Operations Lead, you will partner closely with engineering (fix what breaks, catch it before the customer does), deployment operations (sustain hardware in the field), and deployment strategy (get customers to value, expand, and renew). You’ll also own the customer onboarding experience, giving every Specter user a personalized first impression with the platform. If Deployment Strategy is offense, Customer Operations is defense.

We build hardware and software so our support mandate is much more expansive than a typical SaaS company. About half of what breaks is physical: radio links, site power, mothernodes, firmware, weather. The other half is software and ML: missed detections, false positives, software bugs. Our users span a variety of industries and technical ability.

Your mission is to deliver a support experience that customers and internal teams love, and build the systems that let us do it without linearly scaling our people. If successful, this operational layer will be the foundation on which we build Specters’ physical AI and robotics platform.

## Responsibilities

- Own every customer issue from first report to resolution. Acknowledge issues in minutes, triage, loop in the right on-call engineer or deployment operations lead, keep the customer updated, and close the loop with a root cause.
- Catch issues before our customers do. Live in fleet telemetry and PagerDuty. Own the question “why didn’t we catch this first?” and partner with engineering to close these gaps.
- Understand the details of our product (platform, ML, firmware, hardware, RF). Know the difference between a radio issue, a site power issue, and a bad prompt. Have intuition around when we deploy our team onsite to address.
- Build systems that help us deliver unreasonable hospitality at scale. Meet customers where they are (Slack, Teams, email, text, phone). Remember context from previous interactions. Make our users look good intentionally. Aspire to a “wow, this is beyond what I expected” experience every time.
- Do things agentically. We use Pylon for support issues today but there is a lot to be built that helps us scale excellent support without scaling our people.
- Reduce noise. Distill repeat issues into product features that engineering can build. Minimize anxiety and disruption for customers and internal teams.
- Operationalize technical diligence pre-sales: SLA requirements, integrations, security questionnaires, “can we actually deliver this?” We don’t have a solutions engineering team today. Expect to be helpful pre-sales as needed to ensure we can deliver on customer requirements.

You may be a fit if you:

- Have navigated messy enterprise accounts from early pilots through multi-million dollar expansions.
- Can earn the trust of opinionated engineers (we have many!).
- Have built out processes across product, finance, or customer experience that scale.
- Have good hospitality instincts. Responsiveness, polish, consistency, and sweating the details matter.
- Find joy in distilling complex ideas (customer discovery, technical topics, strategic questions) into what’s essential.
- Can successfully influence product without having direct ownership over it.

## About Specter

## Company Overview
- **One-liner**: Specter builds and deploys long-range wireless sensing networks with AI-powered real-time alerts and semantic search, creating the perception layer for the physical world.
- **Entity Type**: Private (funding stage not publicly disclosed)
- **Headquarters**: Not publicly available (likely US based on website language and job postings)
- **Founded**: Not publicly available
- **Founders**: Not publicly available

## Core Business
- Primary industries: Physical security, critical infrastructure monitoring, industrial IoT, real-time situational awareness
- Target customers: Enterprise and government – including energy companies, data centers, construction firms, ports, stadiums, industrial facilities, and campuses
- Mission statement: "Creating a Software Defined Physical World" – providing instant awareness through real-time alerts, semantic search, and a map-based view of every event

## Products & Services
- **Specter Platform**: A SaaS-based physical intelligence platform that ingests data from long-range wireless sensors (video, thermal, acoustic) and applies general AI (natural language alerts) to detect events such as unauthorized access, safety hazards, equipment anomalies, fires, spills, and perimeter breaches. Features include semantic search, live and historical event detection, and complete situational awareness dashboards.
- **Long-Range Wireless Sensing Network**: Proprietary hardware and software for rugged, wide-area coverage without trenching – deployed across refineries, deserts, offshore platforms, construction sites, and other harsh environments.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Annual revenue not publicly available; company is actively hiring (Software Engineer – Systems listing) and has a live product across multiple industry verticals.
- **Notable Investors/Partners**: Not publicly available
- **Growth Signals**: Recent website updates as of June 2026; expanding to new use cases (energy, data centers, construction, ports, stadiums); job openings indicate scaling engineering team.

## Competitive Advantages
- **Long-range wireless sensing** that eliminates blind spots without trenching or on-site personnel – a differentiator for remote and harsh environments.
- **General AI with natural language alerts** – users set and query alerts in plain English, lowering the barrier for security and operations teams.
- **Multimodal sensing** (video, thermal, acoustic) combined with real-time analytics for high-fidelity event detection (e.g., PPE compliance, spills, equipment theft, person-down incidents).
- Focus on **critical infrastructure** where downtime or security gaps carry high stakes, creating deep vertical-specific moats.

## Strategic Focus
- Expanding horizontal deployment across energy, data centers, construction, logistics, and campus security.
- Deepening AI capabilities through real-time semantic search and event detection to replace traditional CCTV monitoring.
- Building a “software-defined physical world” that unifies disparate sensors into a single intelligent layer.

## Why Work Here
- Opportunity to work on cutting-edge AI + IoT systems that monitor real-world infrastructure at scale.
- Engineering culture likely emphasizes distributed systems, computer vision, edge computing, and high-reliability software (based on job description for Software Engineer – Systems).
- Fast-paced startup environment with a clear product-market fit across multiple verticals.
- Remote/hybrid policy not explicitly stated; job posting does not specify location, but likely offers flexibility.

## Sources
1. [specter.co](https://specter.co/)
2. [specter.co/product](https://specter.co/product)
3. [specter.co/industries](https://specter.co/industries)
4. [specter.co/features](https://specter.co/features)
5. [jobs.ashbyhq.com - Software Engineer – Systems](https://jobs.ashbyhq.com/specter/fe26a690-7934-46f4-bce2-8d8c5495a0dc)

## Other roles at Specter

- [Optics & Camera Engineering Lead](https://feeny.ai/job/optics-camera-engineering-lead-specter-san-francisco-021ech8bvbse) — San Francisco, CA
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- [Manufacturing Engineer](https://feeny.ai/job/manufacturing-engineer-specter-san-francisco-g75553wbxwx6) — San Francisco, CA
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