Senior AI Security Solution Architect

Job Description

Job Description

Our client, a 3rd-generation management consulting firm. They are now looking to add to their team and are hiring an Senior AI Security Solution Architect to build an AI-driven application security platform that uses agentic AI, static analysis, reachability analysis, and isolated execution to identify, validate, and prioritize application vulnerabilities. As the ideal candidate you must be able to an design and build the platform end-to-end, including the agent runtime, orchestration, vulnerability-analysis workflows, exploit validation, and integration with existing security/DevOps pipelines. The strongest candidate will sit at the intersection of: AI/LLM Agents Software Architecture Application Security
Key Responsibilities

• Architect and build an agentic vulnerability-discovery platform end-to-end.
• Design the LLM agent runtime, orchestration layer, and multi-agent workflows .
• Develop autonomous agents for vulnerability discovery and investigation.
• Build adversarial validation/evaluation loops to verify vulnerabilities before they are published.
• Architect cross-repository code indexing, dependency mapping, and source-to-sink reachability analysis .
• Establish secure, isolated environments for exploit execution and validation .
• Evaluate the platform against labeled vulnerability datasets and measure detection accuracy/quality.
• Integrate validated security findings into Azure DevOps using SARIF .
• Establish production architecture, security controls, hardening standards, runbooks, and operational documentation.

• 7 years of software engineering / architecture experience.
• Proven production experience building LLM-based agent or multi-agent systems .
• Strong experience with:
  • Agent orchestration
  • Tool/API integration
  • Agent evaluation and feedback loops
  • Managing non-deterministic LLM behavior
• Strong software architecture and hands-on engineering background.
• Ability to design production-grade AI platforms , not just prototypes.

• Application Security / AppSec
• Vulnerability discovery and exploit development
• Static Application Security Testing ( SAST )
• Software Composition Analysis ( SCA )
• CodeQL, Semgrep, Joern
• Taint analysis / data-flow analysis
• Code indexing using Tree-sitter, SCIP, or LSP
• Isolated execution using Firecracker, gVisor, or containers
• SARIF and Azure DevOps security integration
• CI/CD security pipelines