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Senior · 5+ years exp
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Where Travel Agencies go to Grow Revenue Protect Margin Scale Profitably. Only Wenrix combines market-proven Predictive Price Assurance and Automation to help you win on price and deliver the most competitive offers at search and post-booking — across EDIFACT, NDC, and LCC.

About Wenrix

Wenrix is a fast-growing travel tech SaaS company which is part of eTraveli group, redefining the financial and operational backbone of the corporate and leisure travel industry. Our proven technology and AI solutions empower the global leading Online Travel Agencies and Travel Management Companies and substantially increase and improve their margins, servicing conversion rates and retention for their end customers. With exponential growth, market leading products, and a deeply experienced team, this is a great moment to join and shape the next chapter of Wenrix.

We're building a new team inside Wenrix R&D. It covers DataOps, DevOps and infrastructure: the cloud, the data platform, CI/CD, observability, and the tooling every engineer, data scientist and analyst here works with. We're adding a versatile senior infra engineer who likes trying things out and pushing them across the whole company.

This is a hands-on senior IC role. You'd be one of the team's first engineers, not its manager.

If you think something here should work differently, whether it's how we ship, how our systems perform, or what they're written in, you research it, prove it, and we roll it out together.

What Will You Do?

  • Developer experience: Build the internal tooling engineers work with every day: dev environments and the AI layer (agents, MCP servers, code assistants)
  • Data platform: Join the team behind our data pipelines. They're high volume, varied, and relied on across the company. Day to day that's Snowflake, dbt, Prefect, data quality and observability
  • Cloud and delivery: Work on our infrastructure as code (AWS, EKS, Terraform) and the path from commit to production: CI/CD, deployments, keeping what's live healthy
  • ML in production: Extend the ML infrastructure our models already run on: training and feature pipelines, serving, monitoring
  • Cost: Keep an eye on cloud spend (data and infra) and find where it can come down without slowing anyone
  • Work with backend engineers, data scientists, analysts and PMs, close enough to the business to understand the problem rather than just receive a task

What You Bring

  • 5+ years of hands-on engineering, with depth in at least one domain
  • Strong coding. We're mostly Python, and we want someone who enjoys writing code
  • A history of crossing domains: the BE who moved into DevOps, the data engineer who ended up owning infrastructure, or the startup engineer who owned everything because there was no one else
  • You can take something from idea to production and pull others along when it's bigger than you. Nobody needs to hand you a ticket
  • Big advantage: experience in one or more of Ops/DevOps, Data Engineering, ML engineering
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