AI Ops Engineer (Product)

About the Position

AI Ops Engineer (Product)

London

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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 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.

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Responsibilities

• Automating customer support: Lead our initiative on automating as much of our technical customer support as possible, leveraging Kernel’s docs and MCPs, the right kind of AI tooling, and working closely with the engineering team.
• Turning user feedback into evals: Build workflows that turn data issues reported by users into test cases, helping Kernel catch recurring errors and measure improvements.
• Keeping docs current: Build workflows that detect product changes and keep our documentation accurate.
• Making Kernel easier to demo: Build tools that help our sales team prepare and run demos using relevant account data.

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Requirements

• A track record of shipping: You’ve built tools, automations or AI workflows that people use every day, ideally inside a small, fast-moving startup. Around 2–5 years of experience is typical, but what you’ve built matters more than your years. Ex-founders welcome.
• Curious about product: You’re keen to learn how a product/engineering organization works in a fast-paced startup environment.
• AI-tool obsessed: You are constantly testing new models, agents, MCPs and workflows, and you have the judgement to turn them into reliable systems that people actually adopt - but without turning off the “Local LLM” that you were born with (your brain).
• Strong data instincts: You can turn fragmented, messy information into reliable workflows and create feedback loops that keep it trustworthy.
• Can’t unsee inefficiency: You see the company as a connected system; when you find a broken or unnecessarily manual process, your instinct is to understand it, build the fix and make sure it sticks.

Artisanal programming experience is not required for this role, and you don’t need a traditional software engineering background.

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What We Offer

• 💰 Salary: £60,000–£85,000 + equity
• 🗓️ 24 days holiday per year + bank holidays
• 🥕 £450 monthly office dinner allowance
• ✈️ 2 weeks work-from-anywhere
• 🍼 Generous parental leave policy
• 💼 Pension plan
• 💻 Top-spec equipment and central London office
• 🎉 Team events and dinners
• 🚀 Work directly with the founders to deploy AI across a fast-growing company
• 🏆 High-autonomy, high-trust environment with a small team shipping at pace

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Interview Process

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.