Senior SRE / DevOps Engineer (Kubernetes / A2P Messaging)

Build and operate the infrastructure behind a high-volume messaging platform, taking ownership from Kubernetes cluster through observability, deployment and incident response. The platform processes 1 million messages daily with long-lived TCP sessions. You'll work across two sites and be involved in production readiness, migration, and steady-state operation.

• Use AI-assisted engineering where it improves delivery - including infrastructure tooling, automation, documentation and runbooks.
• Build and operate Kubernetes infrastructure across two sites using infrastructure-as-code and automated delivery.
• Design deployment mechanisms that allow long-lived connections to drain gracefully instead of being dropped during releases.
• Take ownership of platform networking, including stable ingress and egress IPs, Layer 4 load balancing, TLS and connectivity coordinated with an external infrastructure provider.
• Build and operate the observability stack: metrics, logs, dashboards and alerting that provide useful signal rather than noise.
• Design monitoring around real production behaviour, including visibility into individual connections and failure modes.
• Own certificate lifecycle, secrets management and platform access control.
• Operate PostgreSQL in a highly available environment, including replication, failover, backups and verified restores.
• Design and exercise backup and disaster-recovery procedures across two sites.
• Work closely with engineers and QA on performance and production-scale load testing, investigating what fails first and why.
• Support the platform during migration and production cutovers.
• Take part in production incident response and from the steady-state phase, a 24×7 on-call rotation.

• Experience with telecom, carrier, messaging or other environments built around persistent network connections.
• Knowledge of SMPP, SIP, SS7 or similar telecom protocols.
• Strong production experience operating Kubernetes on self-managed, on-premise or similarly infrastructure-heavy environments - not only managed cloud services.
• Experience with stateful, long-lived TCP workloads on Kubernetes, including connection draining, stable ingress/egress, Layer 4 load balancing and deployment behaviour.
• Strong Linux and networking fundamentals. You are comfortable diagnosing problems involving routing, NAT, firewalls, MTU, TLS or packet-level behaviour.
• Practical troubleshooting experience with tools such as tcpdump and production network diagnostics.
• Experience designing monitoring and alerting, not only maintaining dashboards somebody else created. You understand what deserves to wake a human up, and what does not.
• Strong infrastructure-as-code and CI/CD experience for containerised systems.
• Ability to work directly with engineers from external infrastructure and network providers.
• Professional English.
• Experience configuring or troubleshooting IPsec connectivity with external parties.
• Experience designing or operating multi-site active-active or active-passive environments.
• Hands-on disaster-recovery exercises rather than DR plans that existed only on paper.
• Performance engineering experience, including Linux kernel or network tuning for high connection counts.
• Security hardening experience, including CIS-style benchmarks, vulnerability management or software supply-chain practices.
• Experience being the first SRE or Platform Engineer on a system and defining how it should be operated.

• Build it and run it: you won’t inherit an infrastructure somebody else designed or throw your work over the wall after launch. You’ll help build the platform and remain close to it in production.
• A genuinely difficult reliability problem: long-lived protocol traffic, stateful connections, two-site infrastructure and production traffic at telecom scale.
• Influence architecture from day one: deployment, observability and operability are design constraints here, not tasks postponed until after development.
• Greenfield infrastructure: you’ll have real influence over how the Kubernetes platform, delivery pipelines, monitoring and operational practices are created.
• Small senior team: short decision paths and direct collaboration with engineers and the solution architect.
• Production ownership: you’ll follow the system through build, migration, hypercare and steady-state operation instead of disappearing after implementation.
• Modern engineering environment: automation and AI-assisted tooling are used where they genuinely improve engineering and operational work.