Software Engineer, Internal Platforms

OpenTrain AI; Northern (KY); Hybrid; USD 120,000 - 155,000; Full time

Job summary

OpenTrain AI is seeking a remote Software Engineer for internal platforms who will own end-to-end development of internal tools powering AI infrastructure. You will collaborate with product, operations, and design teams to deliver scalable, reliable workflows.

The role emphasizes fullstack work across frontend, backend, data modeling, and cloud infrastructure, with a focus on building internal platforms and AI-related operations.

Qualifications

• Experience building production fullstack systems.
• Strong problem-solving ability and ownership mindset.
• Ability to work in ambiguous, fast-moving environments.

Responsibilities

• Design and develop end-to-end fullstack systems for internal workflows.
• Build backend services and APIs with clear contracts and ownership.
• Create high-quality frontend interfaces for internal teams and stakeholders.
• Perform data modeling and database performance optimization.
• Improve platform reliability, observability, and developer experience.
• Debug and resolve production issues while strengthening operational resilience.
• Use pragmatic tradeoffs across speed, scalability, and maintainability.
• Support engineering quality through code reviews, testing, and continuous improvement.

Skills

TypeScript

React

Node.js

PostgreSQL

REST APIs

AWS

Microservices

Serverless

Data labeling workflows

Text generation

AI infrastructure

Tools

NestJS

Job description

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. OpenTrain helps people discover projects shaping modern artificial intelligence, build their profiles, and apply in minutes.

• Create an OpenTrain account for free.
• Apply through OpenTrain AI for this remote engineering opportunity.
• Contribute to work connected to AI-driven infrastructure and data workflows.

About AI Training and Data Labeling

AI training is the human side of building artificial intelligence. People prepare, review, and evaluate examples that help modern models learn, including computer code, text, and generated responses. In this project, your engineering expertise supports internal platforms and infrastructure used for AI-related operations.

• Work on systems supporting computer code programming labeling workflows.
• Contribute to text generation tasks and AI infrastructure.
• Take part in a fast-growing, cutting-edge area of technology.

The Role

This is a high-ownership Software Engineer, Internal Platforms role focused on building and improving the internal tools, services, and workflows that power operations, products, and AI-driven infrastructure at scale. You will contribute to and grow into owning core internal platform systems end to end.

The role is remote and requires candidates to be based in the United States. The source describes it as full-time and also lists contractor and part-time engagement types. The expected commitment is at least 20 hours per week, with a project duration expected to run for 6 or more months.

• Listed compensation: $120,000 to $155,000 USD per year.
• Location: Remote, United States only.
• Experience level: Expert.
• Expected commitment: 20 or more hours per week.
• Expected project duration: 6 or more months.
• Working language: English.
• Native or bilingual English proficiency required.

What You'll Own

You will build scalable fullstack systems and collaborate with product, operations, and design teams to turn ambiguous requirements into reliable platform capabilities. The work combines frontend development, backend services, data modeling, cloud infrastructure, and operational improvements.

• Design and develop end-to-end fullstack systems for critical internal workflows.
• Build clean, scalable backend services and APIs with clear contracts and ownership.
• Create high-quality, performant frontend interfaces for internal teams and stakeholders.
• Perform data modeling and database performance optimization, including schema design and query tuning.
• Improve platform reliability, observability, and developer experience.
• Debug and resolve production issues while strengthening operational resilience.
• Use pragmatic tradeoffs across speed, scalability, and maintainability.
• Support engineering quality through code reviews, testing, and continuous improvement.

Required Qualifications and Technical Skills

Candidates should have experience building or contributing to production fullstack systems through professional experience, internships, or projects. You should bring strong problem-solving ability, attention to detail, an ownership mindset, and comfort working in ambiguous, fast-moving environments.

• Strong TypeScript fundamentals across frontend or backend development.
• Experience with React or a similar frontend framework.
• Backend development experience with Node.js; NestJS is a plus.
• Understanding of relational databases such as PostgreSQL and core data modeling principles.
• Familiarity with RESTful APIs and distributed system communication patterns.
• Exposure to AWS or similar cloud platforms.
• Awareness of microservices, serverless, or event-driven architectures.
• Experience with computer code programming labeling workflows.
• Experience with text generation tasks.
• Subject matter expertise in internal platforms and AI infrastructure engineering.

Preferred Qualifications

The following experience is preferred and can help you contribute to platform engineering and AI infrastructure work more effectively.

• Experience with CI/CD, infrastructure as code, or DevOps workflows.
• Experience building internal developer platforms, operational tooling, or workflow automation systems.
• Exposure to AI-adjacent, data-heavy, or ML-powered products.
• Experience in startup, lab, or high-growth engineering environments.
• Familiarity with monitoring, observability, and platform reliability best practices.

Why This Work Matters

Every major AI system depends on carefully prepared data, human evaluation, and reliable technology. By engineering internal platforms for code programming and text generation workflows, you can help create the systems that enable people and AI models to work together more effectively.

• Work remotely from the United States.
• Apply advanced software engineering skills to AI-related infrastructure.
• Help improve the tools and workflows behind modern AI development.
• Build experience in a rapidly growing technology field.