Support Engineer (AI)

TL;DR

Support Engineer (AI/SaaS): Providing technical support for a leading AI data labeling platform, focusing on diagnosing and troubleshooting software issues, collaborating with product and engineering teams, and improving support processes. Focus on debugging across cloud environments, APIs, browser issues, and containerized systems, while contributing to internal tooling and automation.

Location: Remote (North America, South America, Europe)

Salary: $75,000–$90,000 USD (United States)

Company

hirify.global (ex Heartex) is building the platform that powers the creation, curation, and evaluation of high-quality data for AI, with its open-source product Label Studio being a de facto standard.

What you will do

• Provide technical support to clients via email and support tickets related to Label Studio's installation, configuration, and usage.
• Diagnose and troubleshoot software issues reported by clients, utilizing debugging tools and logs.
• Collaborate closely with Product, Engineering, and Customer Success to drive issue resolution.
• Create internal and external documentation to improve support quality and self-service.
• Proactively identify opportunities for process improvements and contribute to the enhancement of support procedures and workflows.
• Provide structured, high-quality customer updates throughout investigations.

Requirements

• 3–5 years in technical support or support engineering for a SaaS or developer-focused product.
• Strong debugging skills across cloud environments, APIs, browser issues, and containerized systems.
• Proficiency in Python or Javascript programming for scripting and automation tasks.
• Strong understanding of AWS, including services such as EC2, S3, Lambda, and IAM.
• Familiarity with machine learning concepts and frameworks.
• Excellent problem-solving skills and ability to analyze complex technical issues.
• Exceptional communication skills, both written and verbal, with a customer-centric approach.
• Ability to thrive in a fast-paced environment, managing multiple priorities effectively.

Nice to have

• Experience with Kubernetes, container orchestration, or infrastructure debugging.
• Knowledge of ML/AI workflows or data labeling pipelines.
• Familiarity with Agile development methodologies.
• Familiarity with REST APIs and integrating with external services.

Culture & Benefits

• Help leading AI teams build smarter, more accurate systems.
• Opportunity to advance support maturity and contribute to internal tooling and automation.
• Collaborate cross-functionally with engineering, product management, and customer success teams.
• Competitive compensation based on regional compensation market rates across the globe.