Senior Software Engineering Data Program Lead

OpenTrain AI, Inc.; United States; Remote; USD 9,919,000 - 14,878,000; Part time

Job summary

OpenTrain AI, Inc. seeks a part-time program leader to build and run production systems for AI training programs. You will guide workflows, capacity planning, and quality controls across large contributor networks, while communicating progress and risks to AI research customers.

The role emphasizes turning research goals into actionable tasks, managing distributed teams, and delivering reliable delivery systems for datasets, benchmarks, and evaluations.

Qualifications

• Experience leading complex, multi-stakeholder software engineering programs.
• Ability to identify bottlenecks, define metrics, and drive improvements.
• Strong communication skills with customers and stakeholders.

Responsibilities

• Design contributor workflows, review systems, capacity plans, quality controls, and reusable operating playbooks.
• Build team-lead and reviewer systems for programs with 100 to 1,000+ contributors.
• Find bottlenecks, analyze datasets for systematic errors, and fix root causes through clearer instructions and incentives.
• Turn research goals into task specifications and challenge requirements for signals.
• Use Python, SQL, or similar tools for quality sampling, throughput reporting, and operational reviews.
• Communicate quality trends, risks, progress, and recovery plans to AI research customers.

Skills

Program leadership

Quality controls

Risk management

Data analysis

Cross-functional leadership

Customer communication

Tools

Python

SQL

TypeScript

Java

Go

Job description

The Work

You will build and run production systems for software engineering AI training programs. The work turns research goals into dependable workflows for coding datasets, repository-level tasks, agentic trajectories, reinforcement-learning environments, benchmarks, code review, and rubric-based evaluations.

You will lead delivery across quality, throughput, contributor performance, timelines, scope, and cost. You will also work with AI research customers, report progress and risks, create recovery plans, and mentor other program leads.

• Design contributor workflows, review systems, capacity plans, quality controls, and reusable operating playbooks.
• Build team-lead and reviewer systems for programs with 100 to 1,000 or more contributors.
• Find bottlenecks, analyze datasets for systematic errors, and fix root causes through clearer instructions, sequencing, incentives, and review structures.
• Turn research goals into task specifications and challenge requirements, including tasks that may not produce the intended signal.
• Use Python, SQL, or similar tools for quality sampling, defect analysis, throughput reporting, and operational reviews.
• Communicate quality trends, risks, progress, and recovery plans to AI research customers.

What It Pays and Takes

The listing does not provide a pay rate. It is structured as part-time contractor work and requires at least 20 hours each week.

• Workload: 20 or more hours per week.
• Location: Worldwide.
• Language: English.
• Work arrangement: Part-time contractor.
• Experience level listed: Entry level, while the role title and responsibilities call for senior program leadership capabilities.
• Program leadership: Experience leading complex, multi-stakeholder programs in software engineering, technical program management, consulting, finance, startups, operations, or a similar setting.
• Analysis: Ability to identify bottlenecks, define useful metrics, solve problems, and improve production performance.
• Operations: Experience managing distributed teams, contributor networks, marketplaces, or large-scale technical operations.
• Technical review: Ability to read and review code, understand test suites, and assess technical work independently in Python, TypeScript, Java, or Go.
• Communication: Strong customer-facing communication skills, including risk management, expectation setting, and relationship building.

Helpful Background

Experience with software engineering data programs, coding demonstrations, repository-level tasks, agentic workflows, reinforcement-learning environments, benchmarks, code review, or rubric-based evaluation is useful. Familiarity with quality sampling, operational metrics, contributor management, and technical workflow design can help you turn changing research needs into reliable delivery systems.

About AI Training Work

OpenTrain is the hiring and contracting organization for this role and helps people build careers in AI training and data labeling. AI training work uses human-created examples, reviews, and evaluations to improve how artificial intelligence systems write, reason, search, and produce code.