Software Engineer, General

United States Digital Space LLC

Greater London

On-site

GBP 70,000 - 110,000

Full time

14 days+

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Benefits offered by this job

Wellness benefits

Flexible work options

Competitive compensation

Equity

Job summary

United States Digital Space LLC is seeking a backend engineer to build platform services across the Compute and Inference platforms, focusing on multi-cloud orchestration, resource management, and scalable model deployment pipelines.

You will write production-grade Go code, design APIs and data models, and ensure reliability through tests, monitoring, and incident response; the role blends core infrastructure work with product impact and customer collaboration.

Qualifications

2–4 years of backend engineering, platform development, or distributed systems experience.
Proficient in Go with idiomatic patterns and testing.
Strong understanding of RESTful APIs, microservices, and API design.
Experience with PostgreSQL/MySQL, schema design, and transactions.
Familiarity with storage systems and distributed queues (Kafka, RabbitMQ, NATS).
Knowledge of distributed systems concepts, fault tolerance, and retries.
Experience with Docker, basic Kubernetes concepts, and CI/CD pipelines.
Exposure to cloud platforms (AWS/GCP/Azure) and IaC (Terraform) and observability (Prometheus, Grafana).

Responsibilities

Develop RESTful APIs and gRPC services for platform control planes and inference serving.
Design database schemas for platform state, billing, and metrics.
Work with distributed storage and message queues to build reliable components.
Build event-driven architectures for asynchronous processing and scheduling.
Implement monitoring, logging, and alerting for reliability.

Skills

Golang

Distributed systems

REST APIs

gRPC

Docker

Kubernetes

Testing

CI/CD

Git

PostgreSQL

Redis

Kafka

RabbitMQ

NATS

Terraform

Prometheus

Grafana

AWS

GCP

Azure

Tools

Kafka

RabbitMQ

NATS

PostgreSQL

Redis

Docker

Kubernetes

Terraform

Prometheus

Grafana

Job description

About the companythe company is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, the company takes them from concept to production on a single, unified platform.

We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters.

We’re a fast-growing, VC-backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we’re building the next generation of enterprise AI and we’re looking for exceptional people to help us scale.

Who You Are

You’re a solid engineer with 2-4 years of experience building backend systems and platform infrastructure. You write clean, well-abstracted code with proper design patterns and comprehensive test coverage. You’re comfortable working on both the Compute Platform (multi-cloud orchestration, resource management) and Inference Platform (model serving, autoscaling) under the guidance of senior engineers and platform leads.

You have strong proficiency in Golang and understand how to build maintainable, production-grade distributed systems. You take pride in code quality, enjoy collaborating on low-level designs, and are eager to learn from experienced engineers while contributing meaningfully to critical infrastructure components.

You’re product‑minded, you understand how your technical decisions impact developers using the company’s platform and think about the end‑to‑end user experience. You’re a team player comfortable wearing multiple hats one day you’re building product features, the next you’re joining customer calls to understand their deployment challenges, and the day after you’re helping with UI/UX, customer success, documentation and product ops.

What You’ll Do

Platform Development & Implementation

Build and maintain platform services across the company'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

Backend Systems & Distributed Infrastructure

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

Code Quality & Engineering Excellence

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

Technical Skills & Experience* 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

Preferred Attributes

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.

Why Join the company?

Work directly with high‑pedigree founders shaping technical and product strategy.