Senior AI-First Data Engineer
Smartcat
| Company | Smartcat |
| Category | Engineering |
| Location | Armenia - Remote; Europe; Georgia - Remote; Portugal - Remote; Serbia - Remote; Spain - Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 15 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
About Smartcat
Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises.
We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one.
Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale.
Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us.
Join us in unlocking global potential, one human and agent team at a time. Senior Data Engineer (AI-First)
Mission
Data is becoming one of Smartcat’s most strategic assets.
As a Senior Data Engineer, you will help build the intelligence layer that powers decision-making, AI agents, automation, and business operations across the company.
This is not a traditional data engineering role focused solely on pipelines and dashboards.
You will help transform Smartcat’s data platform into an AI-native foundation where business data becomes discoverable, actionable, and consumable by both humans and AI agents. You will partner closely with Data, Product, Engineering, GTM, and AI teams to create a modern data ecosystem that enables self-service analytics, intelligent automation, and agent-driven decision support.
We're currently building a modern greenfield cloud data platform and transitioning from legacy on-premise and batch architectures toward cloud-native, streaming-first infrastructure. This is an opportunity to have a significant impact on how Smartcat scales its data capabilities over the next several years. The role aligns directly with Smartcat's transformation into an AI-native company and agentic platform.
Outcomes
Evolve our architecture into Next Generation Data Platform
Continue building our data architecture into scalable cloud-native AI-first architecture
Lead the transition from batch-oriented pipelines to near real-time and streaming data systems
Improve reliability, observability, governance, and performance across the data stack
Establish engineering standards and best practices for data development
Turn Business Data into AI-Ready Assets
Build data products that can be consumed by AI agents, analytics systems, and business users
Enable semantic layers, metadata management, and knowledge structures that make data more accessible and actionable
Create foundations for agent-driven reporting, forecasting, and business intelligence
Help transform business metrics from static dashboards into living operational systems
Drive AI-First Data Engineering
Use AI to accelerate development, testing, documentation, monitoring, and operational workflows
Design systems that allow AI agents to query, understand, and act on business data safely
Evaluate emerging AI technologies and identify opportunities to increase productivity across the data organization
Help establish Smartcat as an AI-native data organization, leveraging AI to increase productivity and talent density across the company.
Improve Business Intelligence & Data Accessibility
Make analytics simpler and more accessible for non-technical stakeholders
Improve usability and adoption of BI tools s
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