AI Ops Engineer (Business Operations)
Kernel · 🇬🇧 London, United Kingdom
Sponsorship Verification Proof
Employer is on the UK Home Office register of licensed sponsors.
UK Home Office Register of Licensed Sponsors (Skilled Worker route): listed as 'Kernel Limited', London — Skilled Worker; Worker (A rating)
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- Verification category
- Employer on official sponsor register
- Role category
- ML / AI
- Last verified
- 2026-10-25
- First indexed
- 2026-10-24
- Posted date
- 2026-10-22
- ATS / Feed source
- Arbeitnow
Role Description (Excerpt)
About Kernel Agents are starting to sell, buy and operate on behalf of companies. But before an agent can close a deal, qualify an account, route a lead or assess risk, it has to answer a basic question: which company is this? Today, that answer is messy, and no one answers it reliably. Business identity lives across CRMs, ERPs and third-party datasets full of duplicates, missing parent companies, stale addresses and incorrect enrichment. The cost shows up across the enterprise: sales teams miss revenue opportunities because they lack the right account context; operations teams take on avoidable exposure because risk signals are fragmented or wrong; and finance teams end up chasing, writing off, or defaulting on bad debt that should have been caught earlier. Humans have worked around that mess for years. Agents cannot. They need a reliable business identity layer they can trust. Kernel is building that layer: the business registry for agents. We issue a permanent Kernel ID for every business, plus the context an agent needs to act on it. Ops, data and revenue teams at Gong, Legora, Mistral, Canva and Notion already use Kernel on their own systems. Agents are next, and there will be far more of them. We have raised $20M from top VCs and operators at Plaid, OpenAI, Slack and others, and we are growing 10x YoY. The Role We’re looking for an AI Ops Engineer to build the internal systems that help Kernel scale without adding unnecessary manual work. You’ll work across GTM,…
Excerpt only — read the full requirements and apply directly on Kernel's career page. Listing data via Arbeitnow. We do not process applications.