Software Engineer, AI (Level determined by experience)

About this role

Synack’s Penetration Testing as a Service platform manages customers’ attack surfaces by discovering new assets, pentesting for critical vulnerabilities and gaining visibility into the root causes of security risks. We are committed to making the world more secure by harnessing a talented, vetted community of security researchers to deliver continuous penetration testing and vulnerability management, with actionable results.

Synack's PTaaS platform has uncovered more than 71,000 exploitable vulnerabilities to date, protecting a growing list of Global 2000 customers and U.S. agencies in a FedRAMP Moderate Authorized environment. For more information, please visit www.synack.com . We are looking for a Senior Software Engineer (AI), where you'll design and ship AI agents that plan, reason, drive security tooling and surface exploitable vulnerabilities, running autonomously inside sandboxed environments.

It's a hands-on senior role spanning applied AI and cybersecurity. You'll own systems end to end and raise the technical bar for the team around you. Sounds interesting? Keep reading… Please note: This is a remote position based in the UK. We can only hire citizens of the United Kingdom for this role. Given the nature of the work, the role may be subject to nationality, residency and security-clearance checks. Here’s what you'll do Build AI agents that automate penetration testing: planning, tool use, reasoning over findings, and acting safely within scope.

Stand up and run the sandboxed cyber-lab and range infrastructure, containerised on Kubernetes, where these agents execute offensive tooling. Ship features from ideation through production, including evals, guardrails and monitoring. Improve how our agents work: prompting, tool orchestration, evaluation, and cost. Lead code reviews and design sessions, and help the engineers around you grow. Work closely with our security researchers to translate how they hack into how our agents operate.

Here’s what you’ll need 4+ years of software engineering experience Proven ability to build and scale production systems Strong Python, polyglot codebase Fluent or willing to learn Go Hands-on experience building and operating production AI applications using LLMs and agentic frameworks (e.g., RAG, MCP, LangGraph or similar), including tool integration, prompt design, evaluation, guardrails, and token/cost optimization.