Manager, AI Security & Harness Engineering

Job Summary

The Information Security Manager - AI Security & Harness Engineering will lead the technical integration and operational use of advanced AI capabilities across the Information Security program.

This is a hands-on engineering role focused on building secure AI harnesses, workflows, and automation that allow frontier AI models to analyze security data, identify vulnerabilities and attack paths, support threat hunting, evaluate source code and infrastructure, and accelerate validated remediation.

The role will work closely with Information Security, Engineering, Cloud, and DevSecOps teams to move AI capabilities from experimentation into controlled, repeatable production workflows. A key focus will be connecting AI models with enterprise security tools and data sources while maintaining appropriate human oversight, security controls, testing, and governance.

About The Clearing House

The Clearing House Payments Company L.L.C. is a bank-owned industry utility that shapes the payments landscape and provides infrastructure for safe, reliable, and efficient payments. We see an economy where everyone is connected and a future where modern payments make life easier. The Clearing House operates four payment systems: a high-value wire-transfer system (the CHIPS® network), the country's first and largest instant payments system (the RTP® network), an automated clearinghouse network (the EPN® network), and a check image exchange network (the Image Exchange Network). TCH also operates a bank account number tokenization service, runs a payments association known as the TCH Payments Authority, and maintains the rules for private-sector check image exchange through its ECCHO® business line.

Key Responsibilities

• Design, build, and maintain AI harnesses and agentic security workflows that securely connect advanced AI models with security tools, source code, infrastructure, and security data.
• Engineer workflows that use AI to support vulnerability discovery, attack-path analysis, threat modeling, secure code analysis, threat hunting, and remediation validation .
• Integrate AI capabilities with existing security platforms, cloud environments, APIs, development pipelines, vulnerability management tools, and security telemetry.
• Develop automated processes to identify, validate, prioritize, and remediate security vulnerabilities , with appropriate human review and approval controls.
• Build repeatable testing frameworks that enable security teams to use multiple AI models and techniques to independently analyze and validate security findings.
• Partner with Application Development and DevSecOps teams to integrate AI-enabled security analysis into the software development lifecycle (SDLC) and CI/CD pipelines .
• Develop AI-enabled capabilities to analyze AWS and other cloud environments for configuration weaknesses, vulnerabilities, privilege paths, and potential attack chains.
• Work with Security Operations and threat-hunting teams to develop AI-assisted workflows for analyzing alerts, identifying suspicious activity, and accelerating investigations.
• Evaluate emerging frontier AI models, security tools, APIs, and agent frameworks and determine how they can be safely incorporated into the Information Security program.
• Establish technical safeguards for AI workflows, including access controls, data protection, logging, model and tool permissions, testing, validation, and human oversight .
• Measure the effectiveness of AI-enabled security capabilities, including improvements in vulnerability identification, remediation time, analyst productivity, and security coverage.
• Document architectures, workflows, operating procedures, and security controls supporting production AI capabilities.
• Support regulatory, audit, and risk management reviews of AI-enabled security capabilities and demonstrate that implementations operate within established security and governance requirements.

Skills & Experience

• Strong hands-on engineering experience with AI/LLM platforms, APIs, agent frameworks, or AI orchestration and harness technologies .
• Experience developing production solutions using Python and APIs, with the ability to build integrations and automation across security platforms.
• Experience with frontier AI models and platforms such as Anthropic Claude, OpenAI models, Amazon Bedrock, or comparable enterprise AI platforms .
• Strong understanding of AI agents, tool use/function calling, retrieval-augmented generation (RAG), prompt engineering, model orchestration, and automated evaluation .
• Experience integrating AI or automation into cybersecurity, DevSecOps, vulnerability management, application security, or cloud security workflows .
• Strong AWS experience, including familiarity with IAM, networking, security services, APIs, logging, and infrastructure-as-code.
• Familiarity with security technologies such as SIEM/XDR, vulnerability management platforms, endpoint security, source code scanning, cloud security tools, and threat intelligence pl