AI Governance Platform and Automations Engineer

RTX•New York, NY

7d•$107,500 - $204,500•Remote

About The Position

RTX's Enterprise Services Data (ES-Data) group is seeking a Responsible AI Engineer to support RTX’s focus on Responsible AI policy implementation as part of our enterprise-wide AI Governance initiative. This individual will support the RTX AI Governance team within ES-Data and partner with colleagues across RTX businesses to build, own, and scale AI governance capabilities. The role will focus on configuration of AI governance platforms, automation and integration with enterprise systems, reporting and data quality, vendor coordination, adoption/enablement, and operationalization of policy controls. The Enterprise AI Governance Responsible AI Engineer will play a key role in designing, configuring, and maintaining governance workflows, evidence capture, and integrations across our AI/ML ecosystem—ensuring repeatable, auditable, and scalable controls for responsible AI. This position offers the opportunity to work with leading AI governance platforms and tools such as One Trust, Archer, WatsonX while contributing to critical enterprise-wide initiatives.

Requirements

Bachelor’s degree in STEM or a related field, and a minimum of 8 years of relevant experience or an advanced degree with a minimum of 5 years of relevant experience.
Experience architecting integrations and orchestrating automations using standardized patterns that streamline governance processes.
Experience with One Trust - designing and configuring governance workflows and evidence management in enterprise environments
Experience with reporting, including metrics design, automated reporting processes, and data quality and traceability practices.
Experience with Responsible AI and governance frameworks and regulatory trends
Experience operating with minimal oversight, manage moderately sized projects or processes, and coach or delegate work to lower-level professionals.
Experience communicating with and influencing cross-functional teams Legal, Compliance, Security, Data and AI, and Business stakeholders, including solving complex cross-departmental problems

Nice To Haves

Hands-on experience with Archer or WatsonX AI Governance platforms
Certifications such as AIGP, CIPP or CIPM or Responsible AI training
Ability to translate Responsible AI frameworks into operational controls, measurable metrics, and audit‑ready artifacts.
MLOps literacy, including model lifecycle concepts, model monitoring, drift detection, lineage, and dataset governance

Responsibilities

Configure and maintain enterprise AI governance capabilities, standardizing workflows, controls, and evidence practices to ensure consistent execution across teams and business units.
Design and maintain scalable integrations between AI governance capabilities and core enterprise systems. Establish standardized data exchange and event-driven patterns that automate assessments, approvals, evidence capture, and reporting. Continuously reduce manual effort and improve repeatability, reliability, and audit readiness
Enable governance metrics, analytics, and automated reporting processes. Implement data quality and traceability practices to ensure accuracy, consistency, and audit readiness
Translate Responsible AI, privacy, and security policies into operational controls embedded in processes and platform configurations. Maintain a central control library and supporting artifacts in partnership with compliance stakeholders.
Develop enablement materials, training, and onboarding guides. Provide hands-on support and office hours to drive adherence to governance workflows and continuous improvement in execution
Coordinate with platform vendors for configuration guidance, support, and capability enablement. Evaluate functionality against enterprise requirements to keep solutions vendor-neutral and outcomes-focused