Integration & Distributed Systems Engineer
Posted 10 Aug 2026
Advertised as “Integration & Distributed Systems Engineer – Cognitive Twin (human)”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
No salary listed for this role.
Field of studyComputer Science, Electrical Engineering, Robotics (or related)
Study levelBachelor's or higher
At NEURA Robotics we build cognitive robots and Neuraverse, the connected ecosystem where robots, their skills, and the developers who build them come together. The Cognitive Twin is the unified environment where we design robotic applications, visualize their data in real time, and simulate and run them across virtual and real robots — so an application can be built and validated in simulation long before it runs on real hardware.
A twin is only as useful as the connections that keep it in sync with the real world. You own the API-first architecture and the distributed communication layer of the twin — the transport, the real-time bi-directional sync loop, and the symmetric control plane that makes commanding a virtual robot and a physical one behave identically.
Your mission & challenges
Transport & real-time sync: You design the transport — gRPC/Protobuf microservices, compact binary real-time frames, and WebRTC media / data streaming — and the low-latency, high-throughput bi-directional telemetry sync loop between live fleets and the twin.
Symmetric control plane: You build and maintain a single command path so the same controls drive virtual and live targets identically, and stay consistent under load.
Connectivity: You build the connectors and real-time links that keep the twin and its simulator in sync with the robots, controllers, and services around them — including device-data ingestion (Fast DDS) — at consistently low latency.
API-first architecture & SDKs: You design and own the cross-cutting API/SDK layer every area builds on, generating language-agnostic SDKs from the scene definition format so the twin engine embeds cleanly into external developer environments.
Distributed-systems robustness: You set deployment standards — service boundaries, backpressure, failure and reconnection semantics — instrument transport for latency and throughput, and harden services under load.
Contracts & compatibility: You own the binary data-exchange schema and the scene definition format as the shared boundary between frontend, SDKs, and the simulation backend, plus SDK ergonomics, the auth model for programmatic access, and backward-compatibility policy.
What we can look forward to
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A university degree (Bachelor's or Master's) in Computer Science, Robotics, Electrical Engineering, or a related field — or equivalent hands-on experience.
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Several years of relevant experience designing and operating distributed, real-time systems and APIs/SDKs, with a track record of hardening research / prototype code into production services.