Software Engineer - Platform Infrastructure

Reinforced Learning; Town of Tonawanda (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Reinforced Learning is seeking a Software Engineer - Platform Infrastructure to design and build the core infrastructure powering data generation, evaluation, and agentic systems. You will own shared platforms enabling engineers and researchers to run large-scale, human-in-the-loop workflows and automated data pipelines for frontier AI models.

You will collaborate with the founding team to define system architecture, establish engineering best practices, and build scalable, observable

Qualifications

• Experience building production distributed systems.
• Proficiency in Python and/or JavaScript.
• Experience designing and operating cloud environments (AWS or GCP).
• Experience with messaging systems (Kafka, RabbitMQ, Pub/Sub).
• Experience with high-throughput data pipelines and asynchronous processing.
• Strong understanding of system scalability, performance, and reliability.

Responsibilities

• Architect and develop the shared infrastructure powering data generation platforms, HL systems, and evaluation pipelines.
• Build systems capable of processing large-scale datasets and high-throughput workloads with strong reliability guarantees.
• Create reusable infrastructure and APIs for product engineers and researchers to build on core systems.
• Design systems with observability, monitoring, and fault tolerance for production workloads at scale.
• Help define long-term system architecture across data pipelines, compute infrastructure, task orchestration, and storage systems.
• Work closely with engineers and researchers to support new AI experimentation workflows and platform capabilities.
• Define standards for system design, deployment, reliability, and infrastructure operations.

Skills

Distributed systems

Python

Node.js / JavaScript

Cloud: AWS/GCP

Data pipelines

Observability & monitoring

Production ownership

High-throughput workloads

Job description

Overview

As a Software Engineer - Platform Infrastructure at Reinforced Learning, you will design and build the core infrastructure that powers our data generation, evaluation, and agentic systems. You will be responsible for the shared platforms that enable our engineers and research teams to run large-scale human-in-the-loop workflows, evaluation harnesses, and automated data pipelines used to train frontier AI models. This is a highly technical role with broad ownership. You will architect and build foundational infrastructure that many other engineers depend on, ensuring systems are scalable, reliable, and capable of supporting extremely high-throughput workloads. You will work directly with the founding team to define system architecture, establish engineering best practices, and build the infrastructure that supports the next generation of AI development.

Overview

As a Software Engineer - Platform Infrastructure at Reinforced Learning, you will design and build the core infrastructure that powers our data generation, evaluation, and agentic systems. You will be responsible for the shared platforms that enable our engineers and research teams to run large-scale human-in-the-loop workflows, evaluation harnesses, and automated data pipelines used to train frontier AI models. This is a highly technical role with broad ownership. You will architect and build foundational infrastructure that many other engineers depend on, ensuring systems are scalable, reliable, and capable of supporting extremely high-throughput workloads. You will work directly with the founding team to define system architecture, establish engineering best practices, and build the infrastructure that supports the next generation of AI development.

Responsibilities

• Architect and develop the shared infrastructure powering our data generation platforms, human-in-the-loop systems, and evaluation pipelines.
• Build systems capable of processing large-scale datasets and high-throughput workloads with strong reliability guarantees.
• Create reusable infrastructure and APIs that enable product engineers and researchers to build quickly and reliably on top of core systems.
• Design systems with strong observability, monitoring, and fault tolerance to support production workloads at scale.
• Help define long-term system architecture across data pipelines, compute infrastructure, task orchestration, and storage systems.
• Work closely with engineers and researchers to support new AI experimentation workflows and platform capabilities.
• Define standards for system design, deployment, reliability, and infrastructure operations.

Required Qualifications

• Strong experience building production distributed systems or platform infrastructure
• Proficiency in Python and/or JavaScript (Node.js / Next.js) or similar backend technologies
• Experience designing and operating systems in cloud environments (GCP or AWS)
• Experience with message queues and event-driven systems (Kafka, RabbitMQ, Pub/Sub, etc.)
• Experience working with high-throughput data pipelines and asynchronous processing systems
• Strong understanding of system scalability, performance, and reliability
• Experience owning systems running in production

Preferred Qualifications

• Experience building internal developer platforms or shared infrastructure
• Experience supporting large-scale data processing pipelines
• Experience with AI infrastructure, LLM evaluation systems, or ML pipelines
• Experience working at high-growth startups or scaling early infrastructure
• Experience designing human-in-the-loop or workflow orchestration systems