Job Description
This is a remote position.
You’ll be at the forefront of the AI revolution, working with a product that is actively changing how businesses operate.
Role Overview
As an AI Implementation & Support Engineer, you will be the primary technical partner for the customers. You aren't just a troubleshooter; you are the bridge between our cutting-edge AI platform and the real-world business problems our clients face.
You will lead the charge in onboarding new customers, ensuring the system is configured for success, and provide ongoing, high-level technical support to ensure users get maximum value from the platform.
Key Responsibilities
Implementation & Onboarding:
Lead technical integration for new clients, translating their business requirements into platform configurations.
Technical Troubleshooting:
Diagnose and resolve complex issues related to performance, integrations, and system configurations.
Customer Advocacy:
Act as the "voice of the customer", identifying recurring bugs and suggesting feature enhancements.
Strategic Support:
Provide high-touch support for existing clients, utilising AI-guided tools to accelerate resolutions while maintaining a human, empathetic touch.
The "Human Bridge":
Translate technical concepts into business-friendly language for stakeholders.
Issue Management:
Document and escalate critical bugs to engineering while managing customer expectations throughout the fix lifecycle.
The Ideal Profile
Technical DNA:
Proficiency in system troubleshooting, analysis of large data volumes and basic scripting.
AI Literacy:
Understanding of ML fundamentals, AI engineering, and data workflows.
Business Acumen:
Ability to understand a client's ROI goals and align the system to meet them.
Communication:
Exceptional ability to explain
complex system behaviours into clear, actionable insights for business users.
Mindset:
A proactive "fixer" who doesn't just close tickets but solves underlying problems.
Preferred Qualifications
3+ years
in a technical support, implementation, or solutions engineering role (SaaS experience preferred).
Experience working with
AI/ML platforms
or data-heavy enterprise software.
Familiarity with debugging tools (browser dev tools, log aggregators).
Ability to thrive in a fast-paced, "build-as-you-go" environment.