Software Architect

We are hiring a Senior Principal AI Security Architect to lead the technical security design for our AI initiatives-including LLM pipelines, retrieval systems, and agentic AI frameworks-across both our internal corporate and engineering ecosystem and our product. This role is deeply AI productivity and AI engineering-focused: you will architect secure agent behaviors, build guardrails around tool execution, and embed secure AI patterns directly into the software development lifecycle (SDLC).

What You'll Do

Agentic AI & LLM Security

• Architect security controls for AI agents, including action authorization, tool-access policies, and sandboxed execution environments.
• Design agent orchestration patterns that prevent harmful or unintended actions, cross-tenant data access, and context bleed.
• Build verification layers for agent output, chain-of-thought protection, and safe action routing.
• Implement runtime guardrails around prompt injection, reasoning manipulation, self-escalation, and agent decision loops.

AI Integration Into SDLC

• Embed AI security into every stage of the SDLC, including secure model onboarding, threat modeling, automated AI security tests, and gated promotion of AI features.
• Build automated CI/CD checks for LLM features-prompt validation, policy enforcement, adversarial test suites, and red-team scenarios.
• Partner with engineering teams to define secure coding patterns for AI components, model interfaces, retrieval pipelines, and agent workflows.
• Integrate AI behavior monitoring into observability platforms to support detection engineering and post-deployment validation.

Core Architecture & Security Engineering

• Architect secure AI systems: inference services, RAG pipelines, embedding/indexing layers, and vector DBs.

• Build and secure model registries, orchestration systems, and service-to-model communication patterns.

• Conduct deep technical threat modeling for AI features, agent systems, and data flows.

• Partner on design reviews to ensure secure-by-default implementation of AI capabilities in the SaaS platform.

• Lead technical direction across engineering for secure AI adoption and scalable production deployment., * Shape the future of secure AI engineering and agent-based automation within a leading SaaS platform.

• Build foundational architectures that enable powerful, safe, production-grade AI capabilities.

• Influence the strategic and technical direction of high-impact AI initiatives.

• 15+ years engineering or security architecture experience in cloud-native SaaS environments.
• Hands-on expertise with LLM integration, agentic AI workflows, vector databases, and RAG architectures.
• Strong engineering background in AWS/Azure/GCP/OCI, Kubernetes, microservices, and distributed systems.
• Deep understanding of adversarial ML, secure prompt design, agent risk mitigation, and model hardening techniques.
• Proficiency in Python, TypeScript, Go, or similar languages.
• Experience embedding security controls directly into developer workflows and CI/CD pipelines.

Nice to Have

• Experience designing agent permission frameworks, hierarchical agent structures, or multi-step decision pipelines.
• Experience with LangChain, LlamaIndex, or custom-built agent platforms.
• Background in AI red teaming or developing AI-specific testing frameworks.