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AION

Decentralized GPU marketplace for AI

Software Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listedHybrid

About the Job

Requirements

  • The role requires 2–4 years of experience in backend engineering, platform development, or distributed systems.
  • The candidate must be proficient in Golang, including idiomatic Go, error handling, concurrency patterns, and testing.
  • The candidate must understand backend systems fundamentals, including RESTful APIs, microservices architecture, and API design principles.
  • The candidate must have hands-on experience with databases such as PostgreSQL or MySQL, including schema design, query optimization, and transactions.
  • The candidate must be familiar with storage systems such as object storage, block storage, and distributed file systems, and their use cases.
  • The candidate must have experience with message queues such as Kafka, RabbitMQ, or NATS and event-driven architectures.
  • The candidate must understand distributed systems concepts, including consensus, eventual consistency, fault tolerance, and retry mechanisms.
  • The candidate must have experience with containerization using Docker and basic Kubernetes concepts.
  • The candidate must know testing frameworks and practices, including unit tests, integration tests, and mocking.
  • The candidate must be familiar with Git, CI/CD pipelines, and modern development workflows.

Responsibilities

  • Build and maintain platform services across the Compute and Inference platforms, working with senior engineers and platform leads.
  • Implement features for multi-cloud orchestration, resource scheduling, model deployment pipelines, and autoscaling systems.
  • Write production-grade code with suitable abstractions, design patterns, and comprehensive test coverage.
  • Contribute to low-level design, including service APIs, database schema design, data models, and component interactions.
  • Collaborate with senior engineers on high-level design discussions, providing implementation perspectives and feasibility input.
  • Develop RESTful APIs and gRPC services for platform control planes, resource management, and inference serving.
  • Design and implement database schemas for platform state, resource metadata, billing data, and observability metrics.
  • Work with distributed storage systems, message queues, and databases to build reliable platform components.
  • Build event-driven architectures for asynchronous processing, job scheduling, and platform automation.
  • Implement monitoring, logging, and alerting for platform services to support production reliability.
  • Write unit, integration, and end-to-end tests to ensure code reliability.
  • Participate in code reviews, providing constructive feedback and learning from senior engineers.
  • Refactor existing code to improve maintainability, performance, and scalability.
  • Document design decisions, API specifications, and operational runbooks for platform services.
  • Debug production issues and contribute to incident response and post-mortems.
  • Join customer calls to understand deployment challenges and contribute across product features, UI/UX, customer success, documentation, and product operations as needed.

Desired Qualifications

  • Exposure to cloud platforms such as AWS, GCP, or Azure and their core services is a plus.
  • Experience with infrastructure-as-code tools such as Terraform or observability tools such as Prometheus and Grafana is beneficial.
  • Experience managing large-scale HPC clusters using Kubernetes and Slurm for job scheduling, resource allocation, and workload orchestration.
  • Expertise with data pipelines, ETL systems, and large-scale data processing frameworks.
  • Experience with low-level systems programming, including storage systems, Kubernetes operators, operating-system-level software development, or daemon services such as llm-d and system agents.
  • Experience productionizing machine-learning pipelines, batch-job orchestration, model fine-tuning workflows, and Jupyter notebook orchestration systems.
  • Experience packaging software for on-premises deployments or customer VPC installations, emphasizing security, compliance, and operational simplicity.
  • High ownership, self-direction, and a bias for action.
  • Strategic thinking and the ability to connect technical decisions to business impact.
  • Communication and mentoring skills.
  • Ability to thrive in ambiguous, fast-paced environments and early-stage startup culture.

About the Company

AION

Decentralized GPU marketplace for AI

AION operates a decentralized compute marketplace that lets people and businesses contribute idle GPUs to a shared network and earn passive income. Through this platform, users can buy or sell compute power for AI workloads, making high-performance AI infrastructure more affordable and accessible. Unlike traditional, centralized cloud providers, AION monetizes unused computing resources via a marketplace, offering scalable capacity and democratizing access to AI. The company aims to close the AI wealth gap by enabling widespread ownership of AI compute resources, serving tech-savvy individuals and organizations looking to reduce AI development costs. Revenue comes from facilitating transactions between compute buyers and GPU providers.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
2024

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