Enterprise AI Support Engineer — Cross-Product

INTAPP LIMITED; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Training reimbursement

Free lunches

Wellness program

Flexible time off

Family-formation benefits

Volunteer time off

Donation matching

Job summary

INTAPP LIMITED in London is seeking a Client Support Engineer to join our hybrid team. You will investigate and resolve client support requests related to Celeste and cross-product integrations, combining strong troubleshooting with an understanding of AI concepts in production.

You’ll triage model quality issues, document edge cases with clear steps, and feed insights back to Product and Engineering while training first/second-line staff.

Qualifications

• Proven track record providing technical support for enterprise AI products.
• Strong diagnostic skills across APIs, logs and browser-level tooling.
• Experience with AI concepts such as retrieval-augmented generation and agentic workflows.

Responsibilities

• Investigate and resolve client support requests related to Celeste and integrations across product lines.
• Triage and diagnose AI-specific issues including model quality, retrieval and grounding errors.
• Create, prioritize, track, and update issues in Azure DevOps and Jira.
• Reproduce and document edge cases with clear steps and artifacts for engineering.
• Provide structured feedback to Product and Engineering on AI behavior in production.
• Create and maintain knowledge base documentation for Celeste integrations.
• Provide guidance and training to first and second-line support staff.

Skills

Technical support

Troubleshooting

APIs

Logs

Browser tools

Tools

Microsoft Azure DevOps

Jira

Job description

INTAPP LIMITED in London is seeking a Client Support Engineer to join our hybrid team. You will investigate and resolve client support requests related to Celeste and cross-product integrations, combining strong troubleshooting with an understanding of AI concepts in production.

You’ll triage model quality issues, document edge cases with clear steps, and feed insights back to Product and Engineering while training first/second-line staff.