Tech AI Data Delivery Manager

TransPerfect

4d • Remote

About The Position

You'll design and run AI data projects and build the automation behind them, combining deterministic tooling with LLM agents to deliver solutions in quality management, project management, and data analytics.

The role includes building and maintaining hybrid automation, setting up and operating agents in Claude and the company's native enterprise agentic environment, managing data collection and annotation projects, and turning production and quality data into useful reporting. You'll test automation before release, create continuous auditing workflows, and document processes so coordinators and engineers can operate and extend the solutions.

Requirements

• Intermediate JavaScript and Python skills sufficient to build and maintain production automation.
• Hands-on experience building agents in Claude, including projects, skills, connectors, and scheduled tasks.
• Ability to build agents in the company's native enterprise agentic environment and connect APIs using its infrastructure.
• LLM evaluation experience, including prompt and rubric design, calibration against human judgment, and ability to identify confident but incorrect outputs.
• A data analytics background and experience in the data collection or annotation industry.
• Experience managing projects involving external vendors or contributors and multiple stakeholders.
• Comfort making and owning decisions when information is incomplete.

Responsibilities

• Build hybrid automation that combines deterministic components such as scripts, validation rules, trackers, and scheduled jobs with LLM agents for scoring, classification, checking, and reporting.
• Decide which workflow steps should use rules versus models and design the hand-offs between them.
• Set up and run agents in Claude and the native enterprise agentic environment, including task specifications, data and tool connections, schedules, monitoring, and failure handling.
• Design quality assurance workflows, guidelines, rubrics, and scorecards; calibrate automated checks against human reviewers; and convert review findings into measurable, actionable error categories.
• Manage data collection and annotation projects end to end, including scoping, vendors, workflows, tracking, and delivery, and build tools that enable coordinators to run daily operations.
• Collect, clean, and analyze production and quality data, including throughput, rework, error rates, and contributor performance, and create reporting that teams and clients can act on.
• Test automation before release and build continuous auditing workflows to verify quality.
• Document work in concise specifications, tickets, and runbooks so coordinators and engineers can operate and extend it.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed