DevJobs

Senior DevOps Engineer

Overview
Skills
  • Python Python
  • Go Go
  • GCP GCP
  • AWS AWS
  • Azure Azure
  • Kubernetes Kubernetes
  • Helm
  • Terraform Terraform
  • Networking Networking
  • Airflow Airflow
  • controllers
  • operators
  • BigQuery
  • CI
  • IAM
  • Cloud SQL
  • GKE
  • GitOps
  • KCC
  • Kubeflow
  • Conftest
  • Kyverno
  • OPA
  • ArgoCD
  • Ray
  • Dagster
Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul.

Fetcherr is scaling rapidly, and we are transforming our internal infrastructure into a high-velocity, self-service product. This is a senior opportunity to architect the future of our platform, setting the technical standard for how we deliver services while ensuring reliability and developer independence across diverse global markets.

Responsabilities:

  • Self-service enablement: Build secure, automated pathways that accelerate development while keeping organizational standards intact.
  • Architectural modularization: Design Kubernetes-native abstractions — controllers and operators — and decouple infrastructure into independent service lifecycles that support rapid iteration.
  • Everything as code: Treat infrastructure, policy, and configuration with the same SDLC as application software — versioned, reviewed, tested, and CI-gated.
  • Proactive reliability: Own production through robust observability, clear SLOs, and high operational hygiene; define alerting that fires correctly and lead blameless postmortems that fix the system.

Requirements:

  • Strong GCP experience at production scale (GKE, IAM, networking, Cloud SQL/BigQuery). No compromise here.
  • Kubernetes-native mindset: declarative-first, comfortable with controllers and operators, and a platform-engineering instinct for self-service and separation of concerns.
  • Everything-as-code discipline: any code ships through a defined SDLC (versioned, reviewed, tested, CI-gated). Terraform (KCC a plus), Helm, GitOps (ArgoCD or similar) in your toolkit.
  • Software engineering background, or proven strong development ability in Go and/or Python — you write production code, not just glue scripts.
  • Security awareness baked into how you build: least-privilege IAM, secret hygiene, policy and supply-chain gates, not bolted on after.
  • Production-first mindset: you design for reliability, observability, and recoverability, and you own what you ship.

Nice to have:

  • Policy-as-code (OPA/Conftest, Kyverno) and supply-chain/CI security tooling.
  • SLO/error-budget practice and DORA-based delivery measurement.
  • Multicloud experience (AWS / Azure) — GCP is home, but breadth helps.
  • Big Data or MLOps exposure (Airflow, Dagster, Ray, Kubeflow).
  • A point of view on AI-assisted and spec-driven development.
Fetcherr