Customer Success Engineer

Midwest Startups; United States; Hybrid; USD 115,000 - 140,000; Full time

Benefits offered by this job

Equity eligibility

Job summary

Prediction Guard is seeking a Customer Success Engineer to bridge experimental and production AI for enterprise clients. You will implement APIs/SDKs, design secure architectures, and manage account renewals with a focus on risk and value.

The role requires strong Python and LangChain skills, experience with vector databases, and a security‑minded approach to HIPAA/GDPR/OWASP. Location is United States with remote/hybrid options and up to 25% travel.

Qualifications

• Experience writing Python and agentic code with LangChain/SDKs.
• Hands-on with vector databases and deploying Python services.
• Understanding of embeddings, context windows, and prompt engineering.

Responsibilities

• Lead technical implementation of APIs/SDKs within client environments (AWS, Azure, VPC, air-gapped).
• Advise on secure Agentic and RAG architectures using privacy-preserving filters.
• Run renewal management and executive reviews, drive expansion with secure AI deployments.

Skills

Problem solving

Ownership

Communication

Tools

Python

LangChain

SDKs

Vector databases

Claude Code

Cursor

Docker

Kubernetes

AWS

Azure

NIST AI RMF

HIPAA GDPR OWASP

Job description

United States On-site $115k–$140k/yr + Equity Full-Time Engineering Mid-Senior Jun 21

Python LangChain MCP servers Vector databases Agentic code Claude Code Cursor API calls Docker Kubernetes Cloud-native networking AWS Azure RAG (Retrieval-Augmented Generation) OWASP GenAI Project NIST AI RMF HIPAA GDPR AI development fundamentals Embeddings Prompt engineering Executive presentations Account management Technical implementation Security architecture

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.

Seniority:

Entry level Employment type: Full-time Location: Remote/Hybrid, United States with expectation of up to 25% travel Compensation: Salary range $115,000-$140,000 in addition to variable compensation and equity eligibility

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