Software Engineer

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About the role

About Refractal Refractal is an AI security company building the infrastructure organisations need to defend against autonomous AI threats. 2026 has shown that generally capable intelligence is here. The challenge now is modernising security to stop AI-enabled threats, whether they come from internal agents going rogue or from attackers using AI to become more dangerous. Refractal was founded on cybersecurity and AI expertise from MIT, Microsoft, NASA and the U.S. Navy. Our product lets organisations detect AI-enabled threats at low cost without sacrificing detection quality. We take a practical approach to AI risk, combining proven cybersecurity methods with frontier AI security research. Today, we work with governments and organisations that can't afford to get security wrong. We're backed by leading deep-tech and cybersecurity investors and are growing the team to deliver on this mission. The role You'll connect Refractal to the security systems our customers already use, building the integrations and data pipelines that make their security data usable. You'll work closely with our security engineers and with customers to understand their environments and turn their requirements into reliable software. What you'll do • Build and maintain integrations with security and observability tools, including platforms such as Splunk. • Develop pipelines to ingest, validate and transform security data, accounting for inconsistent formats, incomplete records and changing source systems. • Design clear interfaces between integrations and the wider product, working with platform engineers to keep responsibilities well defined. • Make integrations reliable in production through testing, monitoring, useful error messages and safe handling of credentials and sensitive data. • Investigate customer integration issues and turn recurring problems into product improvements, documentation and reusable implementation patterns. Success in your first six months • You've shipped and supported priority integrations that customers can use with clear setup guidance. • The data flows you own handle common failures predictably and make problems straightforward to diagnose. • You've established reusable patterns that make the next integration easier to build and maintain. About you: essential • Experience building and maintaining software, with a clear approach to testing, debugging and code review. • Familiarity with data engineering concepts, including ingestion, transformation, data quality and pipeline reliability. • Experience working with APIs and external systems, including authentication, pagination, rate limits and error handling. • Ability to investigate unfamiliar systems and turn incomplete requirements into a practical implementation. • Clear communication and a willingness to own work through deployment and ongoing support. Nice to have • Experience integrating with Splunk or other SIEM and observability platforms. • Familiarity with security telemetry, event schemas or detection workflows. • Experience with high-volume data processing or customer-facing integration projects. Our values Radical transparency. We believe the best work happens when everyone feels able to give and receive honest, constructive feedback. Public service. We see AI security as a form of public service. Getting the AI transition right means putting the right infrastructure in place to manage the threats that come with it, and our work helps protect the institutions and services society depends on. Fail fast. We test ideas early, seek feedback and learn quickly. We experiment rapidly and change course when something isn't working, without compromising on security. Pragmatism, not dogmatism. We choose approaches based on how well they solve the problem.

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