We're hiring a DevOps Engineer to take ownership of the platform side of our engineering work. The focus is production reliability, day-to-day operations, and steadily maturing how we run infrastructure. Mandate: keep services healthy and reduce operational risk — not greenfield rebuilds and not multi-region expansion.
You'll be joining the platform team behind a large-scale social app serving a global community — web and mobile, used daily by hundreds of thousands of members worldwide. Members communicate, join groups, and follow a live feed of activity from their communities.
Key responsibilities
Own day-to-day production operations: incident response, root-cause analysis, postmortems.
Maintain and evolve our Kubernetes-based platform on AWS — cluster lifecycle, node groups, ingress, networking, RBAC.
Operate real-time media infrastructure based on LiveKit — media server fleet, autoscaling, proxy layer, recording pipeline.
Look after managed PostgreSQL — backups, restore drills, failover testing, query performance.
Own CI/CD on self-hosted GitLab — runners, pipelines, deployment automation.
Run and improve the observability stack — Prometheus, Grafana, Loki, Sentry, Datadog.
Maintain operational documentation as the source of truth: runbooks, ADRs, on-call playbooks.
Drive incremental modernization of the platform — closing operational gaps, improving security posture, replacing manual processes with automation.
What we offer
Salary:
18.000 – 24.000 PLN net / month B2B
15 066 - 20 087 gross/month UOP
Remote first approach
Transparent, async-first, documentation-driven organization
AI engineering approach
What do we need for this position?
Be pragmatic. Doesn't refactor everything on day one; picks battles by impact and risk.
Ownership mindset — comfortable being the person on the hook when production misbehaves, not the person waiting for instructions.
Writes things down. Runbooks, ADRs, postmortems — without being asked twice.
Communicates clearly with engineers across different stacks and with client stakeholders.
Comfortable saying "I don't know yet, but I'll figure it out" — and then actually doing the figuring out.
Asks why before how.
You'll be a great fit if you have:
4+ years running production workloads on AWS, hands-on with EKS, RDS, and the networking stack around them (VPC, NLB/ALB, Route 53, ACM).
Production Kubernetes experience — not tutorial-level. Cluster ops, manifests, ingress, troubleshooting failing pods and networking issues end-to-end.
Solid Linux + Nginx — reading and writing configs, systemd, log analysis, basic performance tuning, comfortable with TLS termination and WebSocket-friendly setups.
Infrastructure as Code experience — reusable modules, state management, working in a team workflow with reviews.
CI/CD pipelines on GitLab CI (preferred) or a comparable platform (GitHub Actions, Jenkins, CircleCI).
PostgreSQL operational basics on a managed service — backups, point-in-time recovery, slow-query analysis, index basics.
Networking competency — VPC routing, TLS, DNS, NLB vs ALB tradeoffs, debugging connectivity issues across layers.
Observability — Prometheus + Grafana in production, a log aggregator (Loki / ELK), and an error tracker / APM (Sentry / Datadog).
Comfortable writing Bash and at least one scripting language (Python preferred).
Secrets management hygiene — AWS Secrets Manager / SSM Parameter Store / Vault.
Availability for occasional production incidents; has written and shared a postmortem.
Polish and English at B2+, written and spoken.
Nice to have:
WebRTC fundamentals — STUN, TURN, ICE, SDP — enough to triage "users from network X can't connect" reports.
LiveKit self-hosted, especially in distributed mode; bonus if you have touched its autoscaling.
Cloudflare beyond DNS — Stream, TURN, R2.
Twilio Programmable Video or TURN.
GitOps tooling — ArgoCD, Flux, Helm / Helmfile.
Apache Kafka / AWS MSK operations.
OpenSearch / Elasticsearch operations.
Lua / OpenResty in Nginx.
PCI DSS exposure.
AWS cost optimization — Savings Plans, right-sizing, S3 lifecycle policies, RI strategy.
Experience self-hosting GitLab, Sentry, or comparable platforms.
Our recruitment process
Culture & mission fit meeting with Recruitment Team (abt. 45 minutes)
AI fluency assessment via AI CRED (aicred.ai) - a short online test measuring competency across 5 AI dimensions
Competency interview with Service Quality Manager and Backend Engineer (abt. 60 minutes)
Interview with the Interim Project Lead (abt. 45 minutes)
If any other step of the recruitment process is necessary, we will inform you!
And finally, the decision - after which we can say "welcome on board."