Senior Production Engineer

Requirements

  • Strong hands-on Python skills for automation and tooling.
  • Experience in SRE, Production Engineering, Platform Engineering, or related fields with production ownership.
  • Proven ability to build automation and diagnostic tooling to improve recovery times and reduce operational toil.
  • Deep knowledge of cloud-native technologies such as Kubernetes, containers, and distributed systems, including their failure modes.
  • Experience with observability platforms like Datadog and strong monitoring intuition.
  • Familiarity with Infrastructure as Code (Terraform) and GitOps deployment workflows (e.g., ArgoCD, GitHub Actions).
  • Knowledge of technology stacks including Java, Go, Kafka, Redis, Snowflake, and Postgres.
  • Strong analytical and problem-solving skills for ambiguous, high-stakes production issues.
  • Product mindset focused on usability, adoption, and documentation of operational tools.
  • Excellent communication skills for collaboration across engineering, operations, and business teams.
  • Self-starter mentality with initiative and minimal supervision.
  • Curiosity and continuous learning mindset; fintech or financial industry experience is a plus.

What You'll Be Doing

  • Owning the health, resilience, and recovery of production systems.
  • Designing and building monitoring and observability platforms to reduce alert fatigue and speed root-cause analysis.
  • Developing automation and self-healing capabilities to reduce mean time to recovery without manual intervention.
  • Analyzing incidents to identify trends and engineer prevention solutions.
  • Creating reusable runbooks, diagnostic tooling, and recovery playbooks.
  • Establishing golden-path operational workflows to simplify safe and reliable engineering practices.
  • Partnering with Platform Engineering on CI/CD pipelines, deployment safety, and infrastructure resilience.
  • Championing Infrastructure as Code, GitOps, and SRE best practices.
  • Measuring production health using SLIs/SLOs/SLAs and driving reliability-focused engineering priorities.
  • Exploring emerging technologies like AI-assisted diagnostics and development tooling.

Perks and Benefits

  • Opportunity to work on a modern cloud-native platform using technologies such as Kubernetes, AWS, Terraform, ArgoCD, Kafka, Redis, PostgreSQL, Snowflake, Datadog, Python, Go, and Java.
  • Be part of a team that treats reliability as a product and values engineering excellence.
  • Direct impact on reducing downtime and operational toil through automation and tooling.
  • Collaborative cross-functional environment with engineering, operations, and business teams.
  • Support for continuous learning and innovation in production system management.
AI Summary ✨

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