Gainsight Staff AI Security Architect responsible for securing AI-powered products and leading threat modeling for LLM-based features. Collaborate cross-functionally to set security architectures and guardrails in a fast-evolving AI environment.
Responsibilities
We’re looking for a full-time Staff AI Security Architect to join our Security team reporting to the Director of Security. This role is a hybrid role based out of our Wrocław, Poland.
This role may require occasional travel (up to 10-25%) for team meetings, training, or company events. This is not a complete list of responsibilities, and the scope of the role may evolve with the needs of the team and business.
Qualification
Nice-to-have skills or experienceHands-on Agentic
Required
8+ years of experience in security architecture, application security, or security engineering, including hands-on experience securing AI/ML or LLM-powered applications.
Deep understanding of AI-specific threats and mitigations, including prompt injection, data leakage, model and supply chain risk, insecure tool or plugin use, and excessive agent autonomy (for example, the OWASP Top 10 for LLM Applications and MITRE ATLAS).
Proven experience leading threat modeling and security design reviews for complex systems and turning findings into clear, actionable architecture requirements.
Strong grounding in cloud-native architecture on a major cloud platform (AWS, Azure, or GCP), including identity and access management, secrets management, data protection, and API security as applied to AI workloads.
Experience designing guardrails and controls for AI systems, such as input and output filtering, access control for retrieval and agent tools, logging and monitoring, and secure handling of sensitive customer data in AI pipelines.
Working knowledge of AI governance and risk frameworks such as NIST AI RMF and ISO/IEC 42001, and the ability to translate them into engineering requirements.
Demonstrated ability to partner with Engineering and Product leaders, influence without authority, and communicate technical risk to executive and non-technical audiences.
Nice-to-have skills or experience:
Hands-on Agentic, MCP, ML engineering background, including experience building or deploying LLM applications, RAG pipelines, custom MCP servers, or agentic systems.
Experience with AI red teaming or adversarial testing of LLM applications and agentic systems.
Experience securing MLOps and model-serving pipelines, including model provenance and training data protection.
Experience supporting enterprise customer security and AI governance reviews for a B2B SaaS product.
