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About This Role:

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.

In this role, you'll play a key role in securing Gainsight's AI-powered products, internal AI tooling, and customer trust by leading threat modeling and security design reviews for LLM-based features and agentic workflows and setting reference architectures and guardrails. This is a great opportunity for someone who thrives in a collaborative, fast-evolving AI-driven environment and enjoys working cross-functionally with teams like Engineering, Product, Data, IT, Legal, and GRC. The ideal candidate brings strong skills in AI/LLM security architecture, threat modeling, and cloud-native security.

What You'll Do:

You will lead threat modeling and security design reviews for LLM-based features and agentic workflows, set reference architectures and guardrails for AI development and adoption, and assess the risks of third-party models and AI vendors.

You will also translate evolving AI risk guidance into practical engineering standards and advise leaders on tradeoffs. This role is for a hands-on senior security practitioner who can influence without authority and explain complex AI risks to both technical and executive audiences.

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.

What We're Looking For:

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.