Systems Architect Engineer

Salary: £63,000 - 103,000 per year

Requirements:

• Distributed real-time system design, proven in production capacity planning, latency budgeting, backpressure, graceful degradation, and failure-mode analysis. You have owned an architecture, not only contributed to one.
• Hard-deadline systems experience where a missed deadline could not be retried away, and the system had to degrade safely instead.
• Data-intensive architecture at scale, event streaming and CDC, high-ingest relational data, object storage, and explicit cost engineering across storage, transactions, and bandwidth.
• Edge↔cloud systems: an offline-capable control path, store-and-forward, reconciliation, and operating a fleet of remote Linux devices in production.
• PostgreSQL experience with schema design, indexing, partitioning, and optimisation; object storage and lifecycle/tiering.
• Kafka + Debezium (CDC), Redis; gRPC + Protocol Buffers, REST, WebSockets.
• Python, FastAPI, Pydantic, authentication and security basics.
• React, Next.js; live/streaming data UIs.
• Docker, GitHub Actions, Ansible, Azure; Linux fundamentals and troubleshooting.
• Monitoring and observability: metrics, tracing, and load/latency testing on the hot path.
• AI-assisted development: skilled with coding agents and LLM-based workflows (Claude Code, Codex) in everyday engineering without dropping the bar on architecture, tests, security, or reliability.
• Ability to justify decisions in numbers: throughput, latency, cost, and failure modes, not preference or fashion.
• High engineering standards: design and code review, secure coding, meaningful tests including load and latency tests, and reliable CI/CD.
• Strong communication and presentation skills: able to explain an architecture clearly to engineers and management and defend it under challenge.
• Start-up mindset: comfortable in a fast-paced environment, with shifting requirements, broad ownership, and willingness to build as well as design.

Responsibilities:

• Own the architecture of the AI4Fibres software platform from cameras and GPU inference on the line, through the on-site tier that keeps production running, to the cloud that carries analytics.
• Set throughput and latency budgets, data contracts, storage and cost models, and failure behaviour.
• Design the production-scale platform end to end: edge line controllers, a site tier that runs the system independently of the cloud, and the cloud tier above it.
• Decide what belongs in each tier and defend where the line falls.
• Size the system from first principles, including per-item time budgets, camera and GPU load, network sizing, headroom, and degraded modes.
• Design contract-first event schemas and schema registry, gRPC/Protocol Buffers, streaming and message queues, batching, backpressure, and idempotency.
• Own high-volume image and sensor storage design, including retention, sampling, tiering, packing, and the associated cost model.
• Design PostgreSQL for sustained high ingest, including schema design, partitioning, indexing, and separating operational from analytical workloads before they collide.
• Design edge-to-cloud resilience with store-and-forward, CDC, Redis, replay, and continuous reconciliation.
• Ensure everything detected is routed, rejected, or accounted for, and checked against physical mass balance.
• Own the design of FastAPI services and React/Next.js operator dashboards with live data views, and build them where needed.
• Handle deployment and operations with Docker, Ansible, GitHub Actions, and Azure, including versioned rollouts, monitoring, observability, and remote diagnostics across an edge fleet.
• Diagnose latency and throughput problems end to end.
• Set engineering standards, review designs and code, and present and defend architectural decisions to management, the board, and non-technical stakeholders.

Technologies:

• AI
• Ansible
• Azure
• CI/CD
• Claude Code
• Cloud
• Docker
• FastAPI
• GitHub
• Kafka
• LLM
• Linux
• Network
• PostgreSQL
• Python
• REST
• React
• Redis
• Security
• gRPC
• Architect
• Flow
• UX UI Design

More:

We are AI4Fibres, and we are building a production-scale platform that connects cameras and GPU inference on the line, site-level systems that must keep production running independently, and cloud analytics above it. The role is in person. We operate in a highly data-intensive, real-time environment where throughput, latency, storage, bandwidth, and failure behaviour are first-class design constraints.

last updated 38 week of 2026