Senior Software Engineer (LLM Ops & Evals)

Own the LLM gateway: routing, provider failover, rate limits, retries, and cost attribution across multiple model providers

Deploy, version and deprecate models across clouds, regions and environments, including quota and capacity planning, managed as infrastructure as code

Build the shared evaluation platform: versioned datasets, experiment tracking, run and result schemas, reporting, and trace linkage back to the run

Own the infrastructure for async and long-running AI workloads

Own observability for AI traffic: latency, retries and fallbacks, token usage, cost and errors, per team and per use case

Take part in the on-call rotation, run incidents, and close the follow-ups

Implement the security and compliance controls the platform is held to: retention, access control, RBAC and SSO

Define and maintain clean integration contracts between the platform and the teams that consume it

Partner with product and ML engineers to turn their requirements into platform capabilities that are self-service rather than a request queue

Comfort with privacy and compliance work: PII handling, anonymisation, retention, access control

Experience with cloud at the infrastructure level and infrastructure as code (we run across Azure and GCP with Terraform)

Experience building platform or shared-service capabilities consumed by multiple internal teams

5+ years in backend or platform engineering, with strong production Python

Experience running a shared service in production: on-call, incidents, postmortems, SLOs

Experience building or running LLM inference infrastructure: a gateway or routing layer with multiple providers, failover, rate limiting and cost attribution

Hands-on experience with observability tools (OpenTelemetry, Grafana), including instrumenting services and designing dashboards and alerts

Judgment: You exercise sound judgment in ambiguous situations, balance speed and accuracy, and adjust priorities proactively

Ownership: You own work end-to-end, anticipate issues, and ensure high-quality delivery without close supervision

Adaptability: You navigate ambiguity calmly, model positive behavior, and help peers adjust through clear communication

Collaboration: You build strong cross-functional relationships and influence peers through expertise, data, and empathy

Growth Mindset: You encourage open feedback exchange and provide clear, balanced feedback that helps others grow

Synthetic data or document anonymisation pipelines

Document AI: VLMs, OCR, structured extraction and the metrics that go with it

Domain experience in audit, accounting or fintech

Temporal or another durable workflow engine

Self-hosted inference, capacity planning, load testing

Experience with LLM or agent evaluation

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