Staff Software Engineer, Core Systems — Edge Kubernetes

Burns Sheehan Limited

City Of London

Hybrid

GBP 130,000 - 170,000

Full time

6 days ago
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Job summary

Burns Sheehan Ltd is recruiting a Staff Software Engineer (Core Systems) to design and build the central scheduling and resource-allocation components for a robotics and life sciences platform in London. The role combines hands-on coding with technical leadership in a small, high-autonomy team.

You'll work across Go and Python, tackle complex optimisation problems, and ensure real-time coordination of constrained resources on edge Kubernetes deployments.

Qualifications

  • Strong backend and distributed systems experience.
  • Experience with Go and Python for production systems.
  • Expertise in optimisation, scheduling and resource allocation.
  • Hands-on with Kubernetes and edge/distributed environments.

Responsibilities

  • Design core scheduling, routing and resource-allocation systems behind the platform.
  • Solve complex optimisation problems using modelling and solvers.
  • Build distributed, event-driven systems operating in real time.
  • Work across Go and Python as core logic moves to Go.
  • Design systems running on Kubernetes in edge environments.
  • Lead architectural decisions and raise engineering quality.
  • Mentor engineers and influence best practices.
  • Collaborate with Product and customers to translate solutions into outcomes.

Skills

Go
Python
Optimisation modelling
Scheduling
Distributed systems
Event-driven architecture
Leadership
Architecture thinking

Tools

Kubernetes
Google OR-Tools
Gurobi
NATS JetStream
Kafka

Job description

Burns Sheehan Ltd is recruiting a Staff Software Engineer (Core Systems) to design and build the central scheduling and resource-allocation components for a robotics and life sciences platform in London. The role combines hands-on coding with technical leadership in a small, high-autonomy team.

You'll work across Go and Python, tackle complex optimisation problems, and ensure real-time coordination of constrained resources on edge Kubernetes deployments.

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