Software Engineer - Backend - UK

Company: Nominal

Location: London, England, United Kingdom

Work arrangement: On-site

Employment type: Full-time

Experience: 2-5 years

Posted: 2026-11-09

Responsibilities

You will architect and evolve distributed systems to ingest, process, and persist high-frequency telemetry and sensor data. You will also own critical backend systems end-to-end, from ingestion pipelines to storage engines and performance tuning in production.

Requirements

The role requires 3+ years of experience building distributed systems with strong proficiency in Go, Rust, or Java. Candidates must have deep familiarity with cloud infrastructure and hands-on experience with storage systems and data processing technologies.

Skills

  • Distributed systems
  • Go
  • Rust
  • Java
  • Cloud infrastructure
  • Kubernetes
  • Docker
  • Terraform
  • Time-series databases
  • ClickHouse
  • Kafka
  • Apache Arrow
  • Flink
  • Spark
  • Data processing
  • Performance tuning

Benefits

  • Unlimited PTO
  • Sick leave
  • Free lunch
  • Snacks
  • Coffee
  • Professional development stipend
  • Annual company retreat
  • Hardware sensor stipend
  • Employee-friendly equity terms

About this role

ABOUT NOMINAL

Engineers today are building some of the most ambitious machines humanity has
ever seen. They should have AI that’s purpose-built for them.

Nominal is building the Hardware Intelligence Platform that gives engineers
increased visibility into complex physical systems, helps them make better
decisions, and ultimately gets their products into the real world faster. It
brings together the systems, data, intelligence, and applications hardware
engineering requires to meet the AI moment. Hardware engineering teams use
Nominal to simulate, test, manufacture, and operate the physical systems that
keep the world moving, from spacecraft and autonomous vehicles to
next-generation energy systems and robotics.

Our customers span aerospace, defense, manufacturing, transportation, energy,
and robotics. They include Anduril, Shield AI, Wisk Aero, Pratt Miller
Motorsports, Antares, and Shinkei Systems, amongst others, alongside programs
within the U.S. Air Force and Navy. Our team draws from SpaceX, Palantir,
Anduril, Applied Intuition, Tesla, and other leading companies, united by a
common mission: giving hardware engineers the tools to build the future with
speed, safety, and confidence. We're a fast-moving team that owns problems
end-to-end, works across disciplines, and thrives at the intersection of
hardware and software.

Some of the world’s leading technology investors, including Sequoia, Lightspeed,
Founders Fund, General Catalyst, Lux Capital, and Insight Partners, are backing
Nominal’s ambition to change how machines are built and operated. We’re looking
for engineers who want to take on hard problems and help make a new generation
of world-changing hardware possible.

ABOUT THE ROLE

Nominal's backend runs on a set of Platform teams that own everything below the
product surface: ingesting and storing the world's hardware data, making it
queryable at scale, and keeping the whole system running across cloud, on-prem,
and air-gapped environments. As a Backend Software Engineer, you'll join one of
these teams and design and build the distributed infrastructure that powers the
telemetry and validation platform, systems that ingest multi-modal data (time
series, video, point clouds, asset and run catalogs), serve it back at high
scale, and hold up under real production load from customers.

This role is ideal for engineers who enjoy working close to the metal of
distributed systems, reasoning about throughput, latency, data models, and
failure, and who want to see their work directly enable real-world hardware.
You'll own critical backend systems end to end, from ingestion pipelines to
storage engines to performance tuning in production.

🚀 WHAT YOU'LL DO

* Architect and evolve distributed systems that ingest, process, and persist
high-frequency telemetry and sensor data.
* Design storage and indexing strategies for large, time-series, and
event-driven datasets with strict performance and correctness requirements.
* Tackle hard problems around scalability, backpressure, fault tolerance, and
data consistency in real-time systems.
* Optimize hot paths, reduce tail latency, and improve reliability as the
system scales with new customers and use cases.
* Collaborate closely with product, infrastructure, and customer-facing
engineers to solve domain-specific problems for cutting-edge hardware teams.
* Influence backend architecture and technical direction, mentor teammates, and
raise the bar for system design across the org.

🔍 WE'RE LOOKING FOR SOMEONE WITH

* 3+ years building distributed systems where performance, reliability, and
operational simplicity matter.
* Strong experience in Go, Rust, or Java, with an emphasis on correctness,
clarity, and long-lived systems.
* Deep familiarity with cloud infrastructure (AWS, GCP, or Azure) and
production tooling like Kubernetes, Docker, and Terraform.
* Hands-on experience designing or operating storage systems: time-series
databases, columnar formats, or analytics engines (e.g., ClickHouse,
TimescaleDB, Druid, InfluxDB, Parquet).
* Experience with streaming or data processing technologies such as Kafka,
Apache Arrow, Flink, or Spark.
* Comfort reasoning about distributed systems tradeoffs: latency vs.
throughput, consistency vs. availability, abstraction vs. control.
* Clear technical communication and a bias toward ownership: you design it,
build it, ship it, and operate it.

✨ BENEFITS/PERKS

* 🏖️ Unlimited PTO and sick leave
* 🍽️ Free lunch, snacks, and coffee
* 🚀 Professional Development Stipend
* ✈️ Annual company retreat
* 🛠️ Hardware sensor stipend
* 📈 Employee-friendly equity terms
* 🏢 In-office 5 days per week

All qualified applicants will receive consideration for employment without
regard to race, color, religion, sex, sexual orientation, gender identity, or
national origin.

About Nominal

Software Development · 201-500 employees · headquartered in Austin, TX · founded 2022

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