About The Job

AI is transforming businesses for the better, but AI companies have a track record of exposing sensitive data, leaking IP, profiting from your domain knowledge, and compromising the trust that companies have built with their customers. Prediction Guard allows companies to take control of their AI transformation without exposing their proprietary data, by bringing a secure, best-in-class AI control plane into their environment. When they deploy Prediction Guard in their existing infrastructure, companies are able to simultaneously unblock developers (who are eager to innovate) and satisfy security and infrastructure professionals (who can get a good night’s rest knowing their data is secure).

Role Overview

As a Customer Success Engineer at Prediction Guard, you will be the primary technical partner for our enterprise clients. You will bridge the gap between "experimental AI" and "production-ready AI" by helping our customers connect MCP servers, manage model risk, infrastructure and agent building. You aren't just a point of contact; you are a technical advisor who ensures our customers have confidence managing their AI ecosystem.

Key Responsibilities:

Technical Boarding and Architecture:

• Lead the technical implementation of Prediction Guard’s API and SDKs within diverse client environments (AWS, Azure, VPC, or Air-gapped).
• Advise on Secure Agentic and RAG (Retrieval-Augmented Generation) architectures that leverage our privacy-preserving filters to protect sensitive corporate data.
• Map client security requirements (NIST AI RMF, OWASP, HIPAA, GDPR) to specific Prediction Guard policy configurations.

Commercial Strategy & Renewal Management:

• Actively monitor client and control plane deployments.
• Utilize best practices in account segmentation to support customers through building and scaling AI agents and applications
• Lead Executive Business Reviews (EBRs) that focus on risk mitigation, secure calls, model risk and time to value of deployed AI through telemetry and alignment to business objectives.
• Identify opportunities for expansion by staying ahead of the client’s AI roadmap—moving them from simple chat bots to complex, secure autonomous agents.
• Act as the Voice of the Customer for our product team, translating field-tested security failures into new product features.
• Lead the entire renewal lifecycle, from identifying "at-risk" accounts early through technical health checks to final contract negotiation and signature.
• Identify opportunities where the client’s growing inference volume or new use cases (e.g., moving from internal RAG to external-facing agents) require higher-tier security features or increased throughput.

Experience:

The Technical Stack

• Language: Comfort working in Python is a must. You should have experience writing agentic code with LangChain/SDKs/etc, working with vector DBs, managing dependencies, deploying Python services like MCP servers, and debugging API calls.
• AI Knowledge: Deep understanding of AI development fundamentals (embeddings, context windows, and prompt engineering). Comfort with and a preference for working with Agentic coding tools like Claude Code or Cursor.
• Security: Familiarity with the OWASP GenAI Project (Prompt Injection, Insecure Output Handling, etc.).
• Infrastructure: Exposure to Docker, Kubernetes, and cloud-native networking.

The Success Mindset:

• The "CXO Whisperer": Ability to explain complex probabilistic AI risks to a risk-averse security executive in a professional setting.
• Problem Solver: You don't just report bugs; you provide a code snippet or a workaround to keep the client moving.
• High Ownership: In a startup environment, you own the success of the account from the initial API key to the millionth secure call.

Why Prediction Guard?

• Impact: You are at the forefront of the most important transition in software: making AI safe for the enterprise and enabling control over AI across clouds.
• Culture: A "Build-Fast, Secure-Hard" mentality where your customer advocacy contributions directly affect the product roadmap.
• Growth: Exposure to the C-suite of Fortune 1000 companies who are looking to us to define their AI security posture.

Compensation & Benefits:

The salary range for this role is between $115-$140k in addition to variable compensation and equity eligibility.

Location:

Remote/Hybrid, United States

Expectation of up to 25% travel