Senior DevOps Engineer

Posted 2 Hours Ago
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Tel Aviv, ISR
Hybrid
Senior level
Artificial Intelligence • Software
The Role
Architect and operate a secure, self-service platform on GCP and Kubernetes. Build controllers, operators, infrastructure-as-code workflows, and GitOps delivery pipelines. Establish observability, SLOs, alerting, reliability, and recoverability standards while leading blameless postmortems. Develop production-quality Go or Python software, enforce security and supply-chain controls, and enable independent service lifecycles across global markets.
Summary Generated by Built In
Description

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.

Skills Required

  • Strong production-scale GCP experience, including GKE, IAM, networking, Cloud SQL, and BigQuery
  • Experience with Kubernetes-native architecture, declarative systems, controllers, and operators
  • Experience with Terraform, Helm, and GitOps tools such as Argo CD
  • Software engineering background or strong production development ability in Go and/or Python
  • Experience implementing least-privilege IAM, secret hygiene, policy controls, and supply-chain security
  • Production experience with reliability, observability, recoverability, and operational ownership
  • Experience with policy-as-code tools such as OPA, Conftest, or Kyverno
  • Experience with SLOs, error budgets, and DORA-based delivery measurement
  • Multicloud experience with AWS or Azure
  • Big Data or MLOps experience with Airflow, Dagster, Ray, or Kubeflow
  • Perspective on AI-assisted and spec-driven development
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The Company
200 Employees
Year Founded: 2019

What We Do

Fetcherr is an algo-based company that revolutionizes the travel industry with its groundbreaking Generative Pricing Engine (GPE), the first of its kind to leverage AI for real-time, market-responsive pricing decisions. Our GPE augments airlines' existing pricing strategies with ultra-granular, high-frequency adjustments, fully automating workflows from pricing determination to fare publishing. Operating non-stop, the GPE identifies untapped revenue opportunities and efficiently distributes updated fares across all channels. Partnerships with Virgin Atlantic, Azul, ATPCO, and INFARE attest to our system's unparalleled capability to enhance revenue while streamlining operations.

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