Light

• We're looking for builders who can take a customer problem from idea to production, wherever in the stack it lives. • At Light, AI writes code and the bottleneck has shifted from writing to thinking, so we want engineers who work end-to-end and ship things that matter. • We are primarily hiring at mid-level for this role. Junior candidates who are exceptional and genuinely AI-native are welcome. Senior candidates will be considered by exception; we have strong technical leadership and the bar is high.

• Run SOC 1, SOC 2 (Type I & II), and PCI DSS compliance programmes • Plan and manage audits, timelines, and auditor relationships • Own evidence collection, review, and submission • Track audit findings and ensure remediation is delivered with engineering • Work with DevSecOps to ensure controls are implemented in: IAM and access management, CI/CD pipelines, Infrastructure as code, Logging, monitoring, and alerting • Maintain and update security and compliance policies and procedures • Own risk registers, exceptions, and compensating controls • Support customer security questionnaires and vendor due diligence • Document controls clearly for auditors, customers, and internal teams • Partner with the Head of Engineering on compliance priorities and roadmap

• Architect the Engine: Design and build a production-grade Agent Runtime that handles tool registration, permissions, timeouts, and retry semantics for autonomous agents. • Define the Standard: Evolve our internal GenAI Client and SDKs to create a "paved road" for product engineers, standardizing how every team at Light interacts with LLMs. • Solve for Trust: Build the "CI/CD for AI", implementing reliability frameworks, golden datasets, and regression testing pipelines that allow us to deploy prompts and agents with confidence. • Expand the Ecosystem: Lead the integration of Light with external platforms via the Model Context Protocol (MCP) and automation tools like n8n. • Governance & Scale: Design the guardrails, rate limits, and caching strategies that ensure our AI infrastructure scales predictably and cost-effectively.