Senior Customer Engineer (AI Security)

Location: Remote within the UK

Company

hirify.global is building an AI security and governance platform that provides visibility and protection across the AI lifecycle, from development to production and autonomous agents.

What you will do

• Translate customer use cases into technical requirements, configurations, integrations, workflows, and production-readiness plans.
• Lead deployment, integration, and troubleshooting across endpoint and MDM environments, IDEs, coding agents, cloud connectors, SaaS integrations, gateways, and runtimes.
• Write scripts, work with REST APIs, configure Docker and Kubernetes deployments, and set up infrastructure in customer environments.
• Investigate complex technical issues, analyze logs, develop mitigations, and provide Engineering with actionable bug reports and reproduction steps.
• Help customers adopt recurring security and operational workflows through workshops, enablement, runbooks, and technical best practices.
• Collaborate with Customer Solutions, Product, Engineering, Research, Security, and Support to improve the deployment experience.

Requirements

• 5+ years of experience in customer-facing technical roles within B2B SaaS, preferably in Solutions Engineering, Professional Services, or Tier 3 Support at a cybersecurity vendor.
• Experience deploying and integrating solutions in enterprise customer environments and troubleshooting production systems.
• Broad expertise across endpoint management, cloud infrastructure, identity and SSO, and networking.
• Hands-on experience with endpoint and MDM tools such as Jamf or Microsoft Intune, and cloud platforms such as AWS, Azure, GCP, or Databricks.
• Strong scripting and integration skills using Python, Bash, or PowerShell, together with REST APIs, Docker, and Kubernetes.
• Strong troubleshooting and communication skills, with the ability to lead technical customer conversations and own escalations through resolution.

Nice to have

• Familiarity with generative AI, LLM applications, RAG, AI agents, AI development pipelines, and MCP.
• Experience integrating with IDEs, coding agents, or AI gateway and runtime infrastructure.
• Experience with CI/CD, infrastructure as code, observability platforms, CRMs, or ticketing systems.