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Salary
≈ $86k – $167k per year (Estimated)
Location
In office (London)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 22, 2026.

Overview
Company
Impact
Profile match
Legl is a London company founded in 2019 that digitises client onboarding and payments for law firms. Its platform handles identity checks, anti money laundering screening and fee collection in one workflow. The company serves British law firms modernising processes that traditionally ran on paper and cheques.

Hi We’re Legl.

Legl is building the operating system for modern legal services.

We help law firms and regulated businesses replace manual, fragmented workflows with intelligent software from client onboarding and compliance to payments, risk, and reporting.

Legal work is high-stake - it’s regulated, complex, and deeply impactful - and our mission is to help regulated firms grow faster, run their businesses more profitably, manage risk intelligently, and deliver great client experiences

We’re backed by leading European VCs, scaling quickly, partnered with over 600 law firms including 50 of the UK’s top 200, launched in the UK and Australia - and entering our next phase of growth.

We Work Best When

  • AI is the central-operating model: not a tool or a future plan - but the way we run.

  • Decisions live with people: you're trusted to make calls and own them.

  • Think deeply, execute quickly: speed and rigour, not speed or rigour.

What You’ll Do

We are builders who take an AI first approach to engineering - we deliberately blur the lines between Engineering, Product, and Design in search for better impact. Put simply - our primary responsibility is to deliver meaningful product & business value quickly.

Senior Engineers at Legl are expected to own customer and business outcomes & ambiguous problem spaces end to end and across the full-stack, shaping problems collaboratively, making informed trade offs, and taking accountability for sustained customer and business outcomes over time.

Strong impact comes from challenging assumptions, grounding decisions in customer context and evidence, and helping teams focus effort on what matters most. Decisions are shaped early and collaboratively using evidence, rapid feedback, and customer context, then owned and executed independently with clear accountability for outcomes. You will drive product and business goals, shaping problems with product & design, grounding decisions in customer evidence and being accountable for results (rather than through- or out- puts).

AI is treated as a core part of the engineering toolkit, not as an experiment or productivity hack. We use AI deliberately to increase leverage, reduce repeated manual work, improve decision quality, and enable both engineers and cross functional colleagues to move faster safely, with strong judgement applied to all outputs.

This Role Is a Great Fit If You…

  • Are product-centric and outcomes-focused. You get in early with PMs and Designers, challenge them to shape the problem, prioritise your effort against customer and business value, and then own delivery yourself.

  • Are AI-first in how you build, and thrive on solving ambiguous problems end to end, quickly, without needing someone to break the work down for you.

  • Use AI to move confidently beyond traditional stack boundaries, but keep your technical judgement sharp.

  • Reach for tools, automation and AI to increase your own impact and to cut repeated manual work for the people around you. It’s a reflex, not an initiative.

  • Actively enable others. You build the tools, patterns and workflows that let Legl prototype, validate and ship quickly, safely and efficiently, and you care about the engineer who comes after you.

  • Care deeply about impact. You enjoy difficult problems, take responsibility for outcomes rather than tasks, and are always looking for a better way to build, ship and improve software.

This Role Is Not a Great Fit If You…

  • Want a well-defined spec and clear boundaries before you start, and treat shaping the problem as someone else’s job.

  • Prefer to stay in one layer of the stack and hand the rest of the moment it crosses a boundary you don’t own.

  • See AI as a nice-to-have rather than a core part of how you work day to day.

  • Measure your work in tickets closed rather than problems solved for customers, or would rather execute someone else’s priorities than push back on and help set them.

  • Focus purely on your own output. Making the team faster and safer is part of the job here, not extra credit.

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