Site Reliability Engineer (SRE)

原始資料於 2026-11-04T15:05:54.759106+00:00 查閱；內容可能已更新，請查看原始職位。

What We're Looking For
We're looking for engineers who combine operational instinct with a builder's discipline.
You should have:
● Strong hands-on Python skills—this is your primary language for automation and tooling.
● Experience in SRE, Production Engineering, Platform Engineering, or a related discipline with direct production ownership.
● Proven track record of building automation and diagnostic tooling that improved recovery times or reduced operational toil.
● Deep familiarity with cloud-native technologies—Kubernetes, containers, distributed systems—and how they fail in production.
● Experience with observability platforms such as Datadog, and a strong intuition for what "good" monitoring looks like.
● Exposure to Infrastructure as Code (Terraform) and GitOps-based deployment workflows (ArgoCD, GitHub Actions, or similar).
● Familiarity with the broader technology stack: Java, Go, Kafka, Redis, Snowflake, and Postgres.
● Strong analytical and problem-solving skills—you thrive on ambiguous, high-stakes production problems.
● A product mindset applied to operational tooling: you think about usability, adoption, and documentation when building internal solutions.
● Excellent communication skills and the ability to work fluidly across engineering, operations, and business stakeholders.
● Self-starter mentality—you identify opportunities, take initiative, and deliver with minimal supervision.
● Curiosity and a continuous learning mindset; fintech or financial industry background is a plus.
The Technology You'll Work With
You'll operate and build on a modern cloud-native platform that includes:
● Kubernetes & AWS
● Terraform & ArgoCD
● GitHub Actions
● Kafka, Redis
● PostgreSQL & Snowflake
● Datadog
● Python, Go, Java
● gRPC & Protobuf
● Internal Platform APIs and Developer Tooling
What Success Looks Like
Within your first year, you'll have made a measurable impact on production reliability. Success looks like:
● Reducing mean time to detection (MTTD) and mean time to recovery (MTTR) across key production systems.
● Building automation that handles a meaningful percentage of incident scenarios without human intervention.
● Becoming a trusted subject matter expert for core platform components and their failure modes.
● Delivering observability and diagnostic tools that other engineers actually use and depend on.
● Establishing SLO baselines and driving engineering investment based on reliability data.
● Spending less of your time—and your teammates time—on repetitive manual toil.
Your impact won't be measured by the number of incidents you respond to—it will be measured by how reliably our systems run and how quickly we recover when they don't.