Senior Solutions Engineer

FOUND is a rapidly growing enterprise focused on AI security solutions. They are seeking a highly technical, customer-facing AI Security Solutions Engineer to support enterprise customers in evaluating and integrating AI security platforms within complex environments.

Responsibilities:

• Partner with Sales to lead technical discovery, product demos, evaluations, and proof-of-concepts
• Support onboarding, deployment, and integration of the platform into enterprise environments
• Advise customers on AI security best practices, adversarial threat mitigation, and secure deployment architectures
• Work directly with security teams, AI engineers, platform teams, and executives to translate technical capabilities into business value
• Collaborate cross-functionally with Product and Engineering to influence roadmap priorities based on customer feedback
• Build reusable deployment patterns, technical documentation, enablement resources, and integration playbooks
• Serve as a technical subject matter expert in AI security, AI infrastructure, and runtime defense
• Support strategic customer relationships and help accelerate enterprise adoption of AI technologies securely

Requirements:

• 6 + years of experience in Solutions Engineering, Security Engineering, Sales Engineering, Customer Engineering, or related customer-facing technical roles
• Strong background in cybersecurity, including cloud security, application security, threat detection, infrastructure security, or AI security
• Experience working with AI/ML systems, LLMs, model deployment, inference infrastructure, or AI application architectures
• Experience supporting enterprise customers in highly technical environments
• Hands-on experience with APIs, integrations, cloud platforms, and deployment workflows
• Ability to communicate complex technical concepts clearly to both executive and technical audiences
• Experience in startup, scale-up, or high-growth environments preferred
• Familiarity with modern AI infrastructure and security tooling strongly preferred
• Candidates may come from AI-native companies
• Candidates may come from AI infrastructure startups
• Candidates may come from cloud security platforms
• Candidates may come from leading cybersecurity organizations
• Candidates may come from platform engineering or DevSecOps environments
• Candidates may come from security consulting or offensive security teams
• Cloud platforms (AWS, GCP, Azure)
• APIs and distributed systems
• LLM infrastructure and AI deployment architectures
• Kubernetes, containers, and modern infrastructure tooling
• Detection engineering, runtime security, or AI guardrails
• Python or scripting experience
• Security testing, red teaming, or adversarial AI concepts