Software Engineer

🕒 July 14

🏢🏡 London – Hybrid

⏰ Full Time

🟢 Junior

🟡 Mid-level

🖥 Software Engineer

👻 Ghost score 61%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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aion

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2025

🤖 Artificial Intelligence

☁️ SaaS

Artificial Intelligence • Cloud Computing • SaaS

aion is the first truly on-demand infrastructure platform for AI builders, providing instant, scalable compute with true on-demand GPUs. The platform simplifies the AI development process by integrating data management, model training, and deployment into one seamless workspace, eliminating delays caused by compute bottlenecks. With a vertically integrated approach to hardware and services, aion aims to empower AI innovators with reliable access to resources, fair pricing, and absolute transparency without commitments or hidden costs.

📋 Description

• Build and maintain platform services across aion's Compute and Inference platforms, working closely with senior engineers and platform leads • Implement features for multi-cloud orchestration, resource scheduling, model deployment pipelines, and autoscaling systems • Write well-maintained, production-grade code with proper abstractions, design patterns, and comprehensive test coverage • Contribute to low-level design (LLD) 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 inputs • Develop RESTful APIs and gRPC services for platform control planes, resource management, and inference serving • Design and implement database schemas for storing platform state, resource metadata, billing data, and observability metrics • Work with distributed storage systems, message queues (Kafka, RabbitMQ), and databases (PostgreSQL, Redis) 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 ensure production reliability • Write comprehensive unit tests, integration tests, and end-to-end tests to ensure code reliability • Participate in code reviews, providing constructive feedback and learning from senior engineers' perspectives • 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

🎯 Requirements

• 2-4 years of experience in backend engineering, platform development, or distributed systems • Strong proficiency in Golang you write idiomatic Go code with proper error handling, concurrency patterns, and testing • Solid understanding of backend systems fundamentals: RESTful APIs, microservices architecture, and API design principles • Hands-on experience with databases (PostgreSQL, MySQL) including schema design, query optimization, and transactions • Familiarity with storage systems (object storage like S3, block storage, distributed file systems) and their use cases • Experience working with message queues (Kafka, RabbitMQ, NATS) and event-driven architectures • Understanding of distributed systems concepts: consensus, eventual consistency, fault tolerance, and retry mechanisms • Experience with containerization (Docker) and basic Kubernetes concepts • Knowledge of testing frameworks and practices (unit tests, integration tests, mocking) • Familiarity with Git, CI/CD pipelines, and modern development workflows • Exposure to cloud platforms (AWS/GCP/Azure) and their core services is a plus • Experience with infrastructure-as-code (Terraform) or observability tools (Prometheus, Grafana) is beneficial • Bonus/ Good to Have • HPC & Cluster Management: Experience handling large-scale HPC clusters using Kubernetes and Slurm for job scheduling, resource allocation, and workload orchestration • Data Engineering: Expertise with data pipelines, ETL systems, and large-scale data processing frameworks • Systems-Level Programming: Experience with low-level systems programming such as storage systems, Kubernetes operators, OS-level software development, or daemon services (llm-d, system agents) • ML Platform Engineering: Experience productionizing ML pipelines, batch job orchestration, model fine-tuning workflows, and Jupyter notebook orchestration systems • Enterprise Deployment: Experience platformizing and packaging software for on-premises deployments or customer VPC installations with emphasis on security, compliance, and operational simplicity

🏖️ Benefits

• High ownership, self driven and biased for action. • Strong strategic thinking and ability to connect technical decisions to business impact. • Excellent communication and mentoring skills. • Thrives in ambiguity, fast-paced environments, and early-stage startup culture. • Work directly with high-pedigree founders shaping technical and product strategy. • Build infrastructure powering the future of AI computers globally. • Significant ownership and impact with equity reflective of your contributions. • Competitive compensation, flexible work options, and wellness benefits