Senior AI Engineer - AI Patch Backporting (remote opportunity, Europe & CIS)

BSc or MSc in Computer Science, Engineering, or a related field. 5+ years in software engineering as a developer, tech lead, or team lead. Demonstrated ownership of complex systems or components. Hands-on experience integrating LLMs in real projects (OpenAI, Anthropic, etc.). Familiarity with common approaches such as RAG, CAG, agents, tool-calling. Strong Python skills, including asyncio / multithreading / multiprocessing concepts. Experience with testing frameworks (pytest, unittest) and a solid testing culture. Experience with database design and querying (PostgreSQL or another SQL database). Experience with database design and querying (MongoDB or another NoSQL database). Experience with CI/CD tooling (Jenkins, GitLab CI, or similar). Experience with test automation. Experience with containerization (Docker). Confident Linux CLI user. Experience supporting or operating services on Linux/Unix VMs. Willingness and desire to use AI development tools (e.g., Cursor). Ability to take loosely defined problem statements and turn them into concrete plans. Strong written communication skills in English. Published research or documented experimentation experience (plus). Experience formulating and testing hypotheses (plus). Data analysis skills (plus). Basic knowledge of the C language (plus). Regular usage of AI engineering tools (Cursor, WindSurf, aider, Claude Code, etc.) (plus).

Own key components such as the Patch Backporter library and benchmarking infrastructure. Design cross-component solutions to previously unsolved problems in automated patching. Integrate solutions into existing CI/CD and automation stack for production use. Design and evolve the architecture and abstractions of the Patch Backporter library. Identify bottlenecks and weak points in current workflows and drive improvements. Design metrics, datasets, and evaluation flows to measure backporter performance. Automate benchmarks in CI and make results stable and comparable. Plan and implement how backporter updates propagate into the broader automation ecosystem. Build Python tools, CLIs, small services, and helpers to accelerate iteration. Improve local dev setups, test harnesses, and engineering processes for research. Collaborate cross-functionally with other engineering teams. Write clear technical documentation, design docs, and experiment logs. Mentor junior engineers and share knowledge on AI, infra, and tooling.