Information Security 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 platforms.
• Understanding of software vulnerabilities, attack paths, secure coding practices, threat modeling, and vulnerability remediation.
• Experience with Git, CI/CD pipelines, Jenkins or similar automation platforms, containers, and modern software development practices.
• Ability to independently prototype new capabilities and then engineer successful prototypes into secure, documented, repeatable production workflows.
• Strong communication skills with the ability to explain highly technical AI and cybersecurity concepts to security leadership, engineers, auditors, and risk stakeholders.
• Knowledge of security and risk frameworks such as NIST Cybersecurity Framework (CSF), NIST AI Risk Management Framework (AI RMF), and secure AI development practices.

Ideal Candidate

The ideal candidate is a security-minded AI engineer rather than a policy and governance manager. Individual should be comfortable writing code, connecting models to tools and data, experimenting with emerging AI capabilities, and translating successful experiments into controlled production solutions. Individual should combine strong software and cloud engineering skills with sufficient cybersecurity expertise to understand how AI can materially improve vulnerability discovery, threat analysis, secure development, and remediation.

Physical Demands and Work Environment: The working environment is generally favorable. Lighting and temperature are adequate, and there are no hazardous or unpleasant conditions caused by noise, dust, etc. Work is generally performed within an office environment, with standard office equipment available. Travel may be required. Candidates will report to the office three days each week. Onsite work requirements may change at any time. 

The anticipated annual salary range for NY-based candidates for this position is up to $140,000. Base salary and position level will be determined by the role, experience, skill set and location. For eligible positions, discretionary incentive compensation may be awarded contingent on personal and company performance. Our benefits program includes medical, dental, vision, life insurance, 401k plan with company contribution and company match, tuition reimbursement and more.