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 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 $20M from top VCs and operators at Plaid, OpenAI, Slack and others, and we are growing 12x YoY.
You'll be a player-coach engineering leader with a spike in technical strategy, you'll own engineering delivery for your team end-to-end - from developing exceptional engineers to solving some of our most difficult engineering problems & setting technical direction.
This is a hands-on leadership role. You'll spend roughly 20% of your time contributing code and 80% leading your team, with that ratio shifting as we scale.
Build, hire, and develop a high-performing engineering team
Help set technical direction and architecture decisions
Work with the engineering to tackle some of our most difficult problems
Own engineering delivery with an emphasis on velocity
Collaborate closely with Product on roadmap and prioritisation
Write code when needed so you'll stay close to the product
We are in the unique situation that our commercial traction is ahead of our product. You’ll play a leading role in moving towards automation in a way that enables us to rapidly scale with increased complexity and specific customer nuances.
You have extensive experience in architecting enterprise-level systems, delivering on ambitious product visions, and building world class engineering teams.
You have worked at high-growth businesses, and might have previously started your own company.
You are highly analytical, and thinking proactively through the implications of your decisions, but also have high conviction and understand the importance of moving at pace and shipping often.
You have previously led engineering at a company from its earliest stages, and don’t shy away from the manager role - you know what great looks like, and want to help engineers grow.
8+ years software engineering experience
Track record of hiring and developing strong engineers
Strong production systems background - you've built and scaled things that matter, and you’ve done something hard and lived to tell the tale
Proven experience in distributed systems
Experience operating autonomously in small, high-velocity environments - ideally in a startup
Experience working in a data-focused company or closely alongside a data engineering/ML team - data is core to what we're building at Kernel, and you will play a key role in shaping how we grow that capability
Scaled an engineering team through a growth phase (5 → 20+ engineers), or from Series A to Series C
Technical depth across the stack: NodeJS, Postgres, TypeScript, Kubernetes AI-driven or data-heavy product experience
Understanding of LLMs (e.g., RAG, prompt engineering, evals)
CRM data models or workflow automation knowledge
Hands-on Data Engineering or ML Engineering experience - as data becomes an increasingly large part of what we do, this would be a great asset for us to have
Insist on shipping pixel-perfect code
Prefer managing from a distance without technical involvement
Need extensive process and structure before making decisions
If you over-rely on AI coding tools (Cursor, Claude Code) to the point where you don’t read or understand your own code
If you on the other hand don’t understand how these tools (Cursor, Claude Code, etc.) can be force multipliers for senior engineers if used correctly
If you prefer fully remote work
If you don’t like early-stage startup pace
If you’re seeking a purely ‘hands-off’ role
Backend: AWS, NodeJS, TypeScript, Postgres, Clickhouse, Kubernetes
Frontend: NextJS, TypeScript, Tailwind
You don't need to know everything, but you should be comfortable diving into any part of the stack.
We will do our best to offer you a ride of a lifetime. It will not be easy, but it will be thrilling.
💰 Salary: £130,000 – £170,000 + 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 scale the systems that power enterprise AI
🏆 High-autonomy, high-trust environment with a small team shipping at pace
We sponsor visas for exceptional candidates and provide relocation support for those moving to London.
Stage 1: Introductory Call (45 minutes)
An introductory conversation covering your professional background and what you’re looking for in your next role.
Stage 2: Hiring Manager Call (30 minutes)
A conversation with Marcus focused on ways of working and team collaboration.
Stage 3: Technical Deep Dive (60 minutes)
An in-depth discussion exploring your architectural thinking and past technical decisions.
Stage 4: Leadership Scenario Interview (60 minutes)
An onsite interview at our London office, where we’ll walk through real challenges you’d likely face in the role.
Final Stage: Founders Interview
A conversation with our co-founders, Anders and Marcus, focused on values alignment and long-term vision.
Upon mutual fit: references and offer stage.