AI Ops Engineer (Product)

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 and writing off 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 KERN 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 Checkout already use Kernel on their own systems. Agents are next, and there will be far more of them.

We have raised $14M from top VCs and operators at Plaid, OpenAI, Slack and others, and we are growing 5x YoY.

We’re looking for an AI Ops Engineer for our product team to build the internal systems that help Kernel scale without adding unnecessary manual work.

You’ll work across Product, Customer Support, and Engineering - finding the highest-leverage problems and building practical AI-powered workflows.

This is a hands-on builder role. You’ll take ideas from a vague business problem to a tool or workflow that people use, then maintain and improve it in production. You’ll choose the fastest sensible approach for each problem - coding agents, automation platforms, APIs, data pipelines or lightweight code.

Your focus area will be whatever is the most critical blocker for Kernel’s growth, whether that’s automating our customer support, tying our data feedback loop to automatically seed our evals (benchmarks), building tooling for our sales team to demonstrate Kernel, and so on.

You’ll report to Marcus Henglein, our co-founder who leads our Product, Engineering, and Client Delivery teams.

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    Prefer deep specialization over breadth: this role means switching between projects and teams, depending on business needs

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    Prefer steady-state work over project-based sprints: priorities will shift as the business evolves

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    Only want “strategic” work: you will personally build the tools, clean the data and fix the workflows

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    Need every task to be clearly scoped before starting: ambiguity and learning on the fly are constant

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    Avoid operational grunt work or lose interest after the prototype

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    Want to work in a more structured 9-to-6 environment or in a remote/hybrid setup: we are in the office together 4–5 days a week and the pace is high

Stage 1 – Video call with the Hiring Manager.

Stage 2 – Case study interview (in person) with the team.

Stage 3 – Values interview with the Founders.

If there is mutual fit, we move to references and offer.