In simple speak, we make software that helps patients and clinics diagnose, plan and visualize what they can do to physically improve their looks. We're VC funded and have been around for years, looking for only the best engineers to join our London.
This is an in-office role and we’re looking for someone who is competent in making engineering decisions, considering the tradeoffs and taking responsibility.
Your Day to Day:
Triage and fix production bugs: diagnose issues like misbehaving segmentation maps or unexpected API timeouts, isolate root causes, and ship robust fixes that prevent recurrences.
Lead refactors and technical decisions: evaluate tradeoffs — for example, whether to rebuild a service as a DAG (Prefect vs Dagster) or keep it as an async microservice — balancing complexity, maintainability, and observability.
Design and evolve backend services: build modular APIs, background job queues, and scalable integrations for AI and CV workloads.
Collaborate cross-functionally: work closely with AI and product engineers to translate prototypes into robust, observable, production-grade systems.
Review, mentor, and raise standards: help teammates reason through design choices, guide PRs, and advocate for sustainable patterns (test coverage, retry semantics, schema versioning).
Contribute to architectural roadmaps: propose and document design RFCs or ADRs; participate in high-leverage discussions on scaling, cost, and maintainability.
Observability & reliability: add metrics, traces, and dashboards to ensure every refactor and new service is measurable, debuggable, and reliable.
Continuous improvement: automate repetitive work, simplify existing flows, and leave each subsystem better than you found it.
In short, some days you’ll be deep in code; others, you’ll be helping define the “why” behind how we build. You’ll have both the autonomy to experiment and the influence to steer technical direction.
What You Have Experience In :
Lead refactors of critical paths: move synchronous web work (uploads, email, CV/LLM jobs) into queues with retries, DLQs, and idempotency; break coupling; pay down debt without downtime.
Design & evolve service boundaries: from monolith-y Django to Python microservices (Django/DRF + FastAPI where it fits), with clean contracts and versioned APIs.
Make data fast & safe: Postgres schema/versioning, replication & PITR, N+1 audits, indexing strategies, read/write split, migrations with zero/near-zero downtime.
Observability first: metrics, logs, traces (OpenTelemetry; SigNoz/Grafana-style), SLOs + error budgets, dashboards & runbooks; incident reviews that lead to real fixes.
Safe delivery: feature flags, blue/green or hot-cold deploys, rollbacks, infra as code; collaborate with DevOps on Docker/K8s/ECS, GitHub Actions, secrets & VPN.
Write crisp ADRs/RFCs; mentor engineers on refactor patterns (strangler-fig, branch-by-abstraction).
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