Senior Site Reliability Engineer (SRE)

SUMMARY

5+ years of software engineering experience, with significant time building backend services in production Go, Python, Java/Kotlin, orTypeScript/Node.js plus meaningful SRE/production-ownership responsibility. Backend engineers who grew into reliability are exactly the profile;infrastructure-only backgrounds without software engineering depth are not.

Strong distributed-systems fundamentals: RPC and API design, idempotency and retry semantics, consistency models, backpressure, and failure-mode reasoning in microservice architectures.

Production database depth: PostgreSQL internals from an application engineer's perspective transactions, isolation levels, locking, indexing, queryperformance and experience with schema evolution on live systems.

Solid, hands-on Kubernetes experience in production: deployments, services, ingress/gateway, ConfigMaps/Secrets, probes, resource requests/limits,HPA, and debugging workloads with kubectl you can own a service's full lifecycle on the cluster, not just its code.

Proficiency with Helm and Kubernetes deployment tooling: authoring and reviewing charts and values, managing releases and rollbacks, and workingwithin CI/CD and GitOps-driven delivery pipelines (we run Flux CD on AKS).

Observability engineering skill: instrumenting code with metrics and distributed tracing (OpenTelemetry or similar), designing SLOs and alerts, anddebugging from telemetry.

Fluency in at least one of Go, Python, or TypeScript at a level where you could pass a backend engineering interview this role writes and reviews realcode.

Understanding of modern auth: OAuth2/OIDC flows, JWTs, and service-to-service authentication enough to debug and harden them.

Ownership mindset and calm under incident pressure; thrives in a fast-paced startup environment.

Excellent communication skills clear RCAs, design documents, and runbooks, and the ability to present incidents and reliability posture toenterprise clients; fluent written English.

Active, demonstrated use of AI tooling (Claude, Cursor, Copilot, or equivalent) as part of your daily workflow.

Requirements

Experience in fintech, trading, payments, or other correctness-critical domains reconciliation, settlement, ledger integrity, or financial datapipelines.

Streaming data platforms (RisingWave, Flink, Kafka, Materialize) and CDC (Debezium) in production.

Durable workflow engines (Temporal or similar).