Job Description

About Limina

Limina is the contextual data intelligence platform built for the AI era. Evolved from Private AI, the world's most accurate PII and PHI de-identification engine, Limina is expanding into a full platform play that governs sensitive data across the entire enterprise AI lifecycle: from classification and redaction through to agentic workflows, RAG pipelines, and real-time data security.

Brands like RBC, Deepgram, and Boehringer Ingelheim already rely on our platform to build on, govern, and deploy AI against their most sensitive datasets. We've been recognized as a Gartner® Cool Vendor™ in Privacy and a World Economic Forum Technology Pioneer, and we’re backed by investors in Toronto, New York, Seattle, and San Francisco.

The Role
This is neither a ticket-routing position nor a software development role. It's a hybrid customer-facing engineering role that places you on the front line with our customers, embeds you in the technical details, and gives you a real opportunity to shape how the product evolves. You will resolve common issues directly, reproduce and scope unfamiliar problems, and engage Solutions Engineering when deeper product, deployment, or code-level expertise is required — all in the context of customers integrating and deploying Limina in their own environments, where the gap between what they're experiencing and what the product is doing isn't always obvious.

The role is ideal for someone who enjoys hands-on technical investigation, communicates clearly under pressure, and wants to help build a support function from the ground up.

What You'll Do

• Own the support queue — triage, troubleshoot, resolve, and escalate with a clear owner and timeline at every stage

• Perform hands-on troubleshooting across the Limina product surface: HTTP API requests and payloads, entity-detection and redaction configuration, file processing, and container deployment in Docker and customer-managed Kubernetes environments

• Distinguish Limina product and configuration issues from problems in customer-owned applications, infrastructure, networks, or third-party systems — and communicate that boundary clearly to the customer

• Escalate suspected defects and complex deployment questions, with a clear summary of customer impact, reproduction steps, and what you've already ruled out

• Maintain runbooks, troubleshooting guides, and self-serve resources based on resolved cases; surface recurring patterns through the product feedback loop

• Define and improve the support processes, standards, and workflows that will scale with the business — this is an early role with real influence over how the function gets built

• Keep customers informed throughout — no tickets that go dark, no resolutions that land without context

What You Bring

• 2+ years in technical support, support engineering, implementation, or another hands-on technical customer role — ideally supporting an enterprise, developer-facing, or API-based product

• Working knowledge of HTTP APIs, including JSON request and response payloads, HTTP status codes, and common failure modes; comfortable reproducing requests using cURL, Postman, Python, or an equivalent tool

• Hands-on Docker experience: running images, mounting files, configuring ports and environment variables, inspecting container status and logs

• Comfort using a Linux command line and exposure to at least one cloud platform (AWS, Azure, or GCP)

• A disciplined troubleshooting approach and strong escalation judgment — you form hypotheses, change one variable at a time, know when to ask for help, and know what the next team needs to act

• Clear communicator across technical and commercial audiences — you can explain a complex issue to an ML engineer and a VP in the same breath

Nice to Have

• Experience supporting enterprise customers in regulated industries such as healthcare, financial services, or privacy/compliance

• Familiarity with Kubernetes concepts; ability to inspect pods, deployments, services, and logs

• Experience with Helm or managed container platforms such as EKS, ECS, AKS, or GKE

• Early-stage startup experience