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LEAP, part of ATI Global (a major LegalTech group), is building AI-powered applications for law firms. This Senior Platform Engineer role focuses on designing and building the engineering and AI platform that enables product teams to ship securely and compliantly without manual bottlenecks.
You will own the design and implementation of a platform architecture centered on a "manage-by-exception" model. Instead of manual reviews and approval meetings, applications continuously report their security, AI, quality, and compliance status—people only intervene when something falls out of policy.
Key responsibilities include:
**Platform Architecture & Infrastructure**
- Turn a defined target architecture into working shared services: build and deployment pipelines, environments, secrets management, LLM gateway, and observability.
- Design a "paved road" that makes the secure, compliant way to build and ship an app the easiest way.
- Own architecture decisions, document them clearly, and evolve the architecture as the business grows.
**Automated Guardrails & Compliance**
- Build automated release gates into CI/CD: security scanning (SAST, dependency, secrets, IaC), SBOMs, and policy-as-code that stops non-compliant deployments.
- Automate evidence collection so every application's release readiness is visible at a glance, with failing or stale evidence flagged automatically.
- Build dashboards that let leaders see the state of every application and step in only on exceptions.
**AI-Powered Tooling**
- Build AI agents and bots that speed up the development cycle—automated code and security review, release-readiness checks, documentation, and developer self-service.
- Remove friction so engineers get environments, keys, access, and answers without waiting on other people.
**AI Governance & Adoption**
- Help build an AI governance framework that shows who is using AI, for what, and what it costs—across both products and internal use.
- Route model usage through a governed LLM gateway with model allow-listing, cost attribution, and usage telemetry.
- Drive adoption of AI coding tools and agents across engineering and the wider business.
**Cross-Team Collaboration**
- Build integrations connecting product teams to platform APIs, internal services, and external AI providers.
- Work with product teams, security, DevOps, legal, quality, and product leaders to agree standards and turn them into working systems.
- Drive adoption of the framework first across application teams, then across the business.
- Run workshops, write clear documentation, and enable others—leading through influence rather than authority.
You will stay hands-on: much of what you design, you will build.
**Requirements**
- Pragmatic architect who designs for reality and ships working increments.
- Automation-first mindset: if a person is checking it, you ask whether a machine could.
- Comfortable working across many teams and building consensus.
- AI-native: you use AI tools every day and have strong views on using them well and cost-effectively.
- Clear communicator who can explain trade-offs to engineers and executives alike.
- Security-minded: you build controls in rather than bolt them on.
- Experience with CI/CD, infrastructure-as-code, security scanning, and observability tools.
- Experience building or working with LLM gateways, AI governance frameworks, or AI agent systems is a plus.
The posting notes that LEAP is inclusive and encourages applications even if you meet some, but not all, of the requirements listed.
