Note: GlobalLogic estimates the starting pay range for this role to be performed remotely in USA is $160,000 - $180,000 and reflects base salary only. This pay range is provided as a good faith estimate and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.

We are looking for a strong Platform Engineer with deep experience in Python backend engineering, distributed systems, cloud infrastructure, and AI/ML execution platforms. This role will help productionize an existing proof-of-concept into a scalable, secure, and maintainable software platform for executing and evaluating algorithms within video game environments.

The engineer will own the core execution platform, including runner services, orchestration, cloud/container infrastructure, asynchronous job processing, CI/CD automation, artifact/log persistence, and system reliability. The work will be performed within Client-owned systems, repositories, infrastructure, and compliance processes.

Requirements

Required Skills

* Advanced Python backend engineering experience.
* Strong distributed systems and asynchronous processing experience.
* Hands-on AWS experience, especially with compute, storage, IAM, queues, containers, and batch-style workloads.
* Terraform / Infrastructure as Code experience.
* Docker and containerized workload execution experience.
* CI/CD experience, preferably with GitHub Actions or equivalent.
* Strong understanding of queues, workers, orchestration, retries, idempotency, and failure handling.
* Experience designing storage systems for logs, artifacts, execution outputs, and metadata.
* Strong Git/versioning knowledge, including branching, commit hashes, reproducibility, and controlled code execution.
* Strong system-level design thinking across multi-service architectures.
* Ability to work inside client-owned repositories, infrastructure, workflows, and security controls.

Preferred Skills

* Experience building AI/ML execution platforms, experimentation platforms, benchmark systems, or model evaluation infrastructure.
* Experience with reinforcement learning, LLM agents, or AI evaluation workflows.
* Experience operating in private network, restricted, or air-gapped environments.
* Experience with NoSQL, object storage, metadata catalogs, or S3-backed persistence.
* Experience with Kubernetes, ECS, AWS Batch, or large-scale distributed workload execution.
* Experience with security controls for third-party or externally developed code execution.

Job responsibilities

* Design and build the core execution / runner engine for game and algorithm execution.
* Architect and implement distributed platform components across runner, renderer, application, and supporting services.
* Build scalable cloud-native infrastructure using AWS services such as compute, storage, queues, IAM, ECS/EKS/Lambda/Batch, and S3.
* Implement Infrastructure as Code using Terraform.
* Develop asynchronous job processing capabilities using queues, workers, retries, and fault-tolerant execution patterns.
* Ensure environment parity between local development and cloud/private infrastructure execution.
* Build and maintain CI/CD pipelines for automated testing, deployment, and long-running workflow execution.
* Design secure and reproducible external code ingestion workflows, including git-based pipelines, SHA pinning, versioning, and controlled execution of externally developed algorithms.
* Design data persistence layers for logs, artifacts, run outputs, and execution metadata.
* Implement reliability patterns including idempotency, concurrency handling, failure recovery, retries, and observability hooks.
* Operate within private, restricted, or air-gapped execution environments as required.
* Collaborate closely with Full Stack and AI Evaluation engineers on APIs, schemas, storage formats, execution lifecycle, and reporting needs.
* Ensure all source code, configuration, tests, and documentation comply with client-defined standards, security policies, and review processes.