Engineering Lead: Scale Enterprise Systems & Team

Sarah Smith Fund; Greater London; On-site; GBP 130,000 - 170,000; Full time

Benefits offered by this job

Salary + equity

London office

Pension plan

Generous holiday

Relocation & visa support

Job summary

Kernel is seeking an experienced, hands-on engineering leader to own engineering delivery for a high-performing team. You will set technical direction, architect complex systems, and drive velocity while contributing code as needed.

You’ll collaborate closely with Product and scale the organization as we grow. This hands-on leadership role focuses 20% on coding and 80% on guiding a talented team through architectural decisions, product alignment, and deployment at scale in a data-intensive

Qualifications

• 8+ years software engineering experience.
• Proven experience in distributed systems.
• Experience operating autonomously in small, high-velocity environments—startups.
• Experience leading engineering at a company from its earliest stages.
• Experience working with data-focused teams (data/ML).

Responsibilities

• Build, hire, and develop a high-performing engineering team.
• Set technical direction and architecture decisions.
• Lead delivery with emphasis on velocity and quality.
• Collaborate with Product on roadmaps and prioritisation.
• Contribute hands-on coding ~20% of the time.

Skills

Enterprise architecture

Team leadership

Startup scale

Architecting distributed systems

Data-focused engineering

Tools

AWS

NodeJS

TypeScript

Postgres

Kubernetes

ClickHouse

Job description

Kernel is seeking an experienced, hands-on engineering leader to own engineering delivery for a high-performing team. You will set technical direction, architect complex systems, and drive velocity while contributing code as needed.

You’ll collaborate closely with Product and scale the organization as we grow. This hands-on leadership role focuses 20% on coding and 80% on guiding a talented team through architectural decisions, product alignment, and deployment at scale in a data-intensive