Note: The job is a remote job and is open to candidates in USA. Highbrow LLC is seeking a Platform Engineer with deep experience in Python backend engineering, distributed systems, cloud infrastructure, and AI/ML execution platforms. The role involves productionizing an existing proof-of-concept into a scalable, secure, and maintainable software platform for executing and evaluating algorithms within video game environments.
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
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
- 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
Company Overview