We are seeking a software engineer to join our Safeguards Foundations team. As a member of this team, you will design, build, and maintain internal review and enforcement tooling used by Safeguards analysts. This includes case queues, content review surfaces, decision/audit logging, and account-actioning workflows. You will work closely with Trust & Safety operations, policy, and detection-engineering teams to turn messy operational workflows into well-designed, durable software.
Responsibilities:
- Design, build, and maintain internal review and enforcement tooling used by Safeguards analysts
- Understand user workflows and establish tooling for well processes that may be distributed across a number of tools and UIs
- Develop the 'base layer' of reusable APIs, data storage, and backend services that let new review workflows be stood up quickly and safely
- Partner with operations and policy teams to understand reviewer pain points, then translate them into clear product improvements that reduce handling time and decision error
- Integrate tooling with upstream detection systems and downstream enforcement infrastructure so that flagged behaviour flows cleanly from signal → human review → action
- Build in the guardrails that sensitive internal tools require: granular permissions, audit trails, data-access controls, and reviewer wellbeing features (e.g. content blurring, exposure limits)
- Instrument the tools you ship , surfacing metrics on queue health, reviewer throughput, and decision quality so the team can see what's working
- Contribute to the Foundations team's shared platform and on-call responsibilities
Requirements:
- 4+ years of experience as a software engineer, with meaningful time spent building internal tools, operations platforms, or back-office products
- Comfortable using agentic coding tools (e.g. Claude Code) as a core part of your workflow, and can direct them to ship well-tested, production-quality software at a high cadence without lowering the bar
- Take a product-minded approach to internal users: you work with the people using your tools, watch where they struggle, and fix it
- Results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Communicate clearly with non-engineering stakeholders and can explain technical trade-offs to operations and policy partners
- Care about the societal impacts of your work and want to apply your engineering skills directly to AI safety
Preferred qualifications:
- Experience building tooling in a trust & safety, content moderation, fraud, integrity, or risk-operations setting
- Experience designing case-management or workflow systems (queues, SLAs, escalation paths, audit logs)
- Experience working with sensitive data and understanding the privacy, access-control, and reviewer-wellbeing considerations that come with it
- Experience with GCP/AWS, Postgres/BigQuery, and CI/CD in a production environment
- Experience using LLMs as a building block inside operational tools (e.g. assisted triage, summarisation, or classification in the review loop)
Representative projects:
- Rebuilding the analyst review queue so cases are routed by severity and skill, with full decision history and one-click escalation
- Shipping a unified account-investigation view that pulls signals from multiple detection systems into a single, permissioned surface
- Adding content-obfuscation and exposure-tracking features to protect reviewers working with harmful material
- Building an internal labelling tool that feeds high-quality ground truth back to the detection and research teams
Salary: £255,000 – £325,000 per year
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