VP, Enterprise AI Safety Platforms & Guardrails

Goldman Sachs; New York (NY); On-site; USD 130,000 - 250,000; Full time

Job summary

Goldman Sachs seeks a Vice President – AI Safety Platforms to architect and lead enterprise AI safety efforts. You will build a unified evaluation framework, real-time guardrail services, and automated governance controls across core platforms.

You will recruit and mentor engineering teams, align with risk and business units, and drive telemetry, logging, and policy enforcement across deployments. The role requires 8+ years in software/ML, leadership of platform infra, and fluency with LLMs,

Qualifications

• Role Level: Vice President or equivalent senior engineering leadership in enterprise software.
• Education: BS/MS in Computer Science, AI, Systems Engineering or related field.
• Engineering Leadership: 4+ years leading ML or software teams building platform infrastructure.
• Software Engineering Depth: 8+ years writing microservices/APIs/enterprise services in modern languages.
• AI & Agentic Expertise: Fluency with LLMs, RAG, function calling, and agentic execution paradigms.

Responsibilities

• Design, build, and lead a unified enterprise agentic evaluation framework.
• Develop real-time LLM guardrail services and automated governance controls.
• Lead safety platform enhancements including telemetry, execution sandboxes, and data logging.

Skills

Senior leadership

Platform engineering

Python

Go/Java/C++

LLMs / AI safety

RAG systems

Education

Bachelor’s or Master’s in CS/AI/Systems Engineering

Tools

NeMo Guardrails

Guardrails AI

Llama Guard

LangSmith

OpenTelemetry

Phoenix

MLflow

Job description

Goldman Sachs seeks a Vice President – AI Safety Platforms to architect and lead enterprise AI safety efforts. You will build a unified evaluation framework, real-time guardrail services, and automated governance controls across core platforms.

You will recruit and mentor engineering teams, align with risk and business units, and drive telemetry, logging, and policy enforcement across deployments. The role requires 8+ years in software/ML, leadership of platform infra, and fluency with LLMs,