Solutions Architect

About the role

Join Noma Security and help shape the future of AI security in a fast-paced, high-impact environment. Noma is building the first comprehensive AI Security and Governance Platform, helping organizations adopt AI and LLMs with confidence and control. As AI becomes core to modern enterprises, we provide seamless visibility and protection across the entire AI lifecycle. Our team works at the intersection of AI, security, and cloud, shaping a new category in a rapidly evolving market. At Noma, you’ll have the opportunity to make a meaningful impact while working with exceptional people on technology that truly matters. We’re looking for a Solutions Architect to bridge the gap between complex AI security challenges and real-world enterprise implementations. In this role, you will work closely with customers, Product, R&D, and Sales to design scalable, secure, and high-impact AI security solutions. This is a strategic, customer-facing, and hands-on role where you will own the technical design of enterprise deployments and play a key part in shaping how our platform delivers value in production environments.

Responsibilities

• Own Customer Solution Design: Lead technical discovery sessions with enterprise customers to deeply understand their AI usage, architecture, and security requirements.
• Own Customer Solution Design: Design end-to-end solution architectures tailored to customer environments (cloud, hybrid, on-prem).
• Own Customer Solution Design: Translate security and governance needs into scalable technical implementations.
• Be the Technical Bridge: Work closely with Sales during pre-sale processes to support technical validation and proof-of-value engagements.
• Be the Technical Bridge: Partner with Product and R&D to communicate field feedback and influence roadmap priorities.
• Be the Technical Bridge: Ensure smooth handover from pre-sale to post-sale implementation and ongoing optimization.
• Drive AI Security Implementations: Architect integrations across AI systems, LLM applications, data pipelines, model layers, and runtime environments.
• Drive