Staff Software Engineer

ABBYY ABBYY · Enterprise · Hungary · R&D (Engineering)

Staff Software Engineer to lead the design and delivery of complex, cross-cutting capabilities for ABBYY's Document AI platform (Vantage), focusing on LLM integrations, compliance, analytics, and platform extensibility. The role involves technical leadership, setting quality standards, strategic collaboration, platform improvement, operational excellence, and mentorship.

What you'd actually do

  1. Drive the technical design and delivery of significant Vantage platform capabilities, from architecture and API contracts through deployment, monitoring, and iteration.
  2. Define and uphold engineering standards for the Vantage codebase – covering code quality, service reliability, performance, security, and compliance – and drive their adoption across teams.
  3. Act as a senior technical voice in cross-functional planning with product management, ML engineering, cloud architecture, and engineering leadership; translate business priorities into actionable technical roadmaps.
  4. Lead initiatives to improve Vantage platform health at scale: service decomposition, observability, CI/CD maturity, and developer productivity.
  5. Own high-severity incident response for Vantage cloud services; drive post-mortems and systemic reliability improvements.

Skills

Required

  • 10–13 years of professional software engineering experience
  • C++
  • C# .NET
  • CI/CD pipelines (GitHub Actions and/or Azure DevOps Pipelines)
  • microservices architecture
  • distributed system design
  • cloud-native patterns
  • mentoring engineers
  • technical design reviews
  • architectural decisions

Nice to have

  • cloud (Microsoft Azure)
  • enterprise compliance
  • security
  • reliability standards
  • workflow-driven systems (orchestration, retries, timeouts, and state management)
  • integrating Machine Learning, Neural Networks or LLMs
  • operating across a globally distributed engineering organization

What the JD emphasized

  • deep expertise in C++
  • microservices architecture
  • distributed system design
  • cloud-native patterns at enterprise scale
  • integrating Machine Learning, Neural Networks or LLMs into enterprise applications and workflows

Other signals

  • document AI platform
  • LLM integration
  • enterprise customers
  • complex problems
  • data extraction
  • classification
  • action on data