data engineer for AI-native platforms

Smartcat is building an AI-powered platform for multilingual content, combining generative AI, human-in-the-loop workflows, and an Enterprise Skill Graph to help companies create, translate, and localize global content at scale. Its platform enables enterprises to build hybrid workforces of humans and AI agents and turn business knowledge into action.

• Evolve Smartcat's data architecture into a scalable, cloud-native, AI-first platform;
• Lead the transition from batch-oriented pipelines to near real-time and streaming systems;
• Improve reliability, observability, governance, and performance across the data stack;
• Establish engineering standards and best practices;
• Build data products consumable by AI agents, analytics systems, and business users;
• Develop semantic layers and metadata management;
• Use AI to accelerate development, testing, documentation, monitoring, and operational workflows;
• Design systems that let AI agents query, understand, and safely act on business data;
• Improve business intelligence and data accessibility for non-technical stakeholders;
• Enable self-service analytics without sacrificing governance or quality;
• Mentor engineers through code reviews, architecture leadership, and knowledge sharing;
• Own a defined piece of architecture or a data product end-to-end;
• Identify and apply AI-powered workflows to accelerate engineering work.

• 6+ Years of experience in Data Engineering, Analytics Engineering, or a related field;
• Proven experience designing and operating modern cloud data platforms, ideally in high-growth SaaS environments;
• Experience working effectively with technical and business stakeholders;
• Ability to lead complex projects from design through delivery;
• Strong hands-on experience with Databricks, dbt, Airflow, Python, SQL, and data modeling;
• Experience with data warehousing architectures, data quality frameworks, data governance, and data orchestration and integration;
• Experience with streaming architectures and event-driven systems;
• Experience with business intelligence platforms, product analytics platforms, and CRM/customer data platforms;
• AI-first mindset with experience using AI for development, automation, debugging, testing, architecture exploration, or documentation;
• Evidence of measurable productivity gains through AI adoption;
• Nice to have: experience building AI-native data products, semantic layers, RAG systems, vector databases, knowledge graphs, or enabling AI agents to consume operational business data.

• Remote-friendly work model;
• Global team across 30+ countries;
• Collaboration through a hub-and-spoke model anchored in eight key locations;
• Work with an AI-powered platform in the multilingual content industry.