Tech Stack

Description

You will help build and scale ABBYY's AI platform, owning how AI services are built, deployed, observed, and evolved in production. You'll design systems, write production code, influence architecture, and mentor engineers.

Requirements

• 10+ years of experience in backend or platform engineering
• Strong proficiency in Python (or similar backend languages)
• Solid experience building microservices and distributed systems
• Hands-on expertise with Kubernetes in production environments
• Strong understanding of DevOps and MLOps principles
• Experience with data management for ML (datasets, labeling, pipelines)
• Cloud experience with Azure or strong willingness to adopt Azure quickly
• Ability to think at system level and still deliver hands-on

Responsibilities

• Design and build scalable AI platform services using Python and microservice architectures
• Own DevOps and MLOps workflows including CI/CD, model deployment, versioning, and rollback
• Build and maintain Kubernetes-based platforms for AI workloads
• Work on data pipelines, dataset versioning, and auto-labeling workflows for model training
• Enable end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring
• Collaborate closely with ML researchers, product teams, and other platform engineers
• Drive best practices in software design, reliability, security, and observability
• Lead technical discussions, review designs, and mentor team members