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Kernel gives enterprise RevOps teams confidence in their CRM data.
We’ve raised a $14M Series A from top VCs and operators at Plaid, OpenAI, Slack and others to build the AI-native alternative to Dun & Bradstreet’s entity and hierarchy data.
RevOps teams at Gong, Navan, Zip, Remote and GoCardless use Kernel to clean, enrich and complete their CRM data at enterprise scale, eliminating duplicates, fixing hierarchies and restoring trust in the foundation that powers forecasting, territory planning and AI initiatives.
Our platform combines entity-level intelligence with mass-action tooling to give RevOps teams the data quality and control needed to plan confidently and deploy AI successfully.
The RoleYou are a backend-oriented engineer with strong experience in database infrastructure, IaC, and large-scale data systems. You will work closely with product and engineering to ensure Kernel’s infrastructure can handle massive data and parallel execution at scale.
You thrive in a fast-moving environment where solving complex data and scaling challenges is the norm, and you enjoy thinking deeply about systems reliability, cost efficiency, and performance.
Designing and scaling real-time write/read paths balancing OLTP and OLAP needs
Implementing Infrastructure-as-Code for reproducibility and rapid iteration
Optimizing Postgres replication, sharding, and indexing strategies
Improving data flow between operational and analytical stores
Hardening Kubernetes queues and scheduling heavy jobs efficiently
Ensuring system observability and SOC2-level reliability
Driving cost efficiency through infra modelling and autoscaling
Producing technical artifacts: replication diagrams, freshness matrices, baselines
6+ years of backend or infrastructure engineering experience
Hands-on experience with Postgres replication, partitioning, indexing, sharding
Strong background in AWS (Aurora/RDS, S3, EKS, autoscaling, networking)
Experience with Infrastructure-as-Code (Terraform, Pulumi, or equivalent)
Exposure to large-scale data pipelines or ML workloads
Comfort working autonomously and solving systemic infra issues
Experience with analytical databases (Redshift, Clickhouse, BigQuery)
Familiarity with search/retrieval infra (Elasticsearch, vector DBs)
Monitoring and observability experience (Datadog, Grafana, Prometheus)
Knowledge of event streaming systems (Kafka, Kinesis)
Understanding of RAG or hybrid retrieval systems
Want only pure product feature work — this role leans deep into infra
Need long-term roadmaps and heavy structure
Focus mainly on DevOps tooling without database fundamentals
Prefer fully remote work (this role requires at least 3 days a week in the office)
Don’t enjoy high-intensity infra challenges in an early-stage environment
Want to manage rather than build
We will do our best to offer you a ride of a lifetime. It will not be easy, but it will be thrilling.
💰 Salary: £120,000 – £200,000 + equity
🗓️ 24 days holiday per year + bank holidays
✈️ 2 weeks work-from-anywhere
💼 Pension plan
💻 Top-spec equipment and central London office
🍽️ Free dinner at the office
🎉 Team events and dinners
🚀 Work directly with the founders to scale the systems that power enterprise AI
Core DB: Postgres (partitioning, replication, JSONB)
Infra: AWS, Kubernetes, Terraform, Pulumi
Analytics: Redshift, Clickhouse
Backend: NodeJS, TypeScript
Workflow automation: n8n
Fara Ashiru, Head of Engineering
Sam Houghton, Founding Engineer
Eleanor Leung, Senior Engineer
David Saltares, Senior Engineer
Stefan Sabev, Head of Product
Tom Ankers, Senior Engineer
Willis Chou, Senior Engineer
We sponsor visas for exceptional candidates and provide relocation support for those moving to London.
Interview ProcessStage 1 – 30-minute intro call with Sandi to discuss motivations and strengths.
Stage 2 – Take-home task (≤ 4 hours).
Stage 3 – 90-minute technical interview reviewing your solution in our London office.
Final Stage – Founders interview with Anders (CEO) and Marcus to explore values alignment.
If there is mutual fit, we move to references and offer.
Kernel AI London, England Office
128 City Road, London, United Kingdom, EC1V 2NX



