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Automation Engineer (Customer Service)

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Remote from
Europe
Salary
Undisclosed
Employment
Full Time
Experience
Open level
Published
Apply before
1 Nov 2026
Listing views
180
Application actions
13
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AI Summary

The role, at a glance.

Nebius seeks an Automation Engineer to reduce manual Customer Service workload through scalable backend automations and self-service flows. The role centers on Python development, REST API integrations, LLM-powered agents, N8N workflows, and integrations with Jira, billing, and internal systems. Key work includes automating quota requests, billing and data-subject request flows, notifications, and tooling for cluster operations. This is a software engineering role embedded in a customer-service domain, with significant ownership in a fast-growing AI cloud environment.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe role requires production-quality Python automation across several APIs, workflow systems, and LLM agents, where reliability and safe handling of customer-facing operations are essential. Rapid ticket-volume growth and cross-functional integrations increase the technical and operational complexity.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$130,000
US market range$105k–$160k
AI insightNo salary range is disclosed; "Competitive compensation" is not a usable compensation figure. Estimated US-market annual base salary for a mid-level Automation Engineer with Python, systems-integration, workflow automation, and LLM-agent experience is $105,000-$160,000 USD, with an estimated median of $130,000 USD; this is a market estimate, not an offer from Nebius.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design an automated quota-request workflow that is reliable and auditable?

I would define the request states and validation rules first, then build an API-driven workflow with idempotency keys, structured logs, retries with backoff, and clear escalation paths for exceptions. I would persist decisions and API responses for auditability, expose metrics for throughput and failures, and roll it out gradually with human review for edge cases.

What considerations are important when deploying an LLM agent for support engineers?

I would constrain the agent with approved tools, scoped permissions, retrieval from trusted documentation, and structured outputs. I would add prompt-injection defenses, redaction for sensitive customer data, human approval for consequential actions, evaluation datasets, and monitoring for quality, latency, cost, and unsafe behavior.

Describe your approach to integrating multiple REST APIs into an event-driven automation.

I begin by documenting authentication, rate limits, schemas, error semantics, and ownership for each API. I use a normalized internal data model where appropriate, validate payloads, make handlers idempotent, and implement durable retries or dead-letter handling so temporary failures do not lose customer requests.

How would you decide whether to use N8N, a Python service, or a workflow engine such as Temporal?

I would use N8N for straightforward, visible integrations and notification flows that benefit from rapid iteration. I would choose a Python service for custom logic, testing depth, or performance needs, and Temporal for long-running, stateful workflows requiring durable execution, retries, and complex compensation logic.

How do you measure whether a customer-service automation is successful?

I would establish a baseline for manual handling time, ticket volume, resolution time, error rate, and escalation rate. After release, I would track automation completion rate, customer and agent feedback, cost per request, reliability metrics, and any quality regressions, then prioritize improvements based on impact and risk.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

About Nebius:

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

About the team

The Customer Service team at Nebius handles thousands of requests every month — quota applications, billing operations, planned enterprise cluster upgrades, and incident notifications. Volume has grown 130% over seven months and continues to grow alongside our customer base.

We are building a dedicated automation team to turn repetitive manual work into scalable, maintainable systems: LLM-powered agents, self-service flows, and infrastructure tooling.

The role

We are looking for an Automation Engineer to design and build systems that move repetitive Customer Service work into automated flows. You will work directly with ticketing system data, build LLM agents, develop self-service flows, and integrate solutions with internal Nebius systems.

Your responsibilities will include:

  • Build agents and scripts to automate quota request processing — the largest single category of manual engineer work in the queue
  • Develop self-service flows for billing and DSR requests: payment method updates, account deletion, marketing opt-out, invoice retrieval
  • Build and maintain LLM-powered agents that help support engineers handle complex tickets in real time
  • Develop N8N workflows for customer notifications and event-driven processes
  • Integrate solutions with Jira API, billing API, and internal Nebius systems
  • Contribute to tooling for planned cluster operations (Terraform, runbooks)
  • Maintain and improve existing automation as ticket volumes grow

We expect you to have:

  • 3+ years of software engineering experience with a focus on automation, backend development, or system integrations
  • Strong Python skills
  • Hands-on experience working with REST APIs and integrating external systems
  • Practical experience with LLM APIs or building AI agents
  • Understanding of how to build reliable, maintainable automation systems
  • Working proficiency in English

It will be an added bonus if you have:

  • Experience with N8N, Temporal, or similar workflow automation tools
  • Knowledge of Jira API or other ticketing systems
  • Experience with Terraform or cloud infrastructure
  • Understanding of Kubernetes and containerization
  • Background in support engineering or adjacent functions

Benefits & Perks:

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and ownership
  • Collaborative and innovative culture
  • Opportunity to work on impactful AI projects
  • International environment and talented teams

What’s it like to work at Nebius:

Fast moving – Bold thinking – Constant growth – Meaningful impact – Trust and real ownership – Opportunity to shape the future of AI

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.

If you need accommodations during the application process, please let us know.

Apply now >

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