Overview
An early-stage engineering team is building an AI-focused platform for large-scale data processing and model evaluation, and is looking for a senior engineer to help shape it from the foundation up. The work spans agentic systems, high-volume data pipelines, and automated evaluation — architecture meant to stay reliable and defensible at scale, not just perform in a demo.
This is a role with wide ownership. You'll design core systems, build and operate the data layer end to end, and partner closely with the engineering lead on the hard technical calls. It's equal parts architecture and hands-on operations — you should be as comfortable designing a system as you are debugging one in production.
Responsibilities
- Design and build agentic systems and automation from scratch, including automated evaluation loops that let the system measure its own success and iterate faster.
- Own large-scale data pipelines: high record volumes, control groups, statistical validation, and full traceability of how data flows through the system.
- Apply workflow orchestration to keep complex, high-throughput processing reliable under real load.
- Take on hands-on work when the day calls for it — SQL, custom reports, and direct fixes.
- Act as a technical counterpart for architecture and design reviews.
- Flexible Work Environment: Opportunity to work remotely.
- 1:1 English Classes: Individual English language training to enhance your communication skills.
- Premium Medical Insurance: Comprehensive health insurance to ensure your well-being.
- Great Team: Work with a supportive, collaborative, and dynamic international team.
- Equipment Provided: All necessary equipment supplied for efficient job performance.
- Accounting Support: Full accounting assistance in Ukraine and Poland.
- Paid Time Off: 18 days of Annual Vacation and 7 days of Sick Leave without a doctor's note.
- Flexible payment system, which allows you to withdraw funds in one click and has about twenty withdrawal options.
Requirements
- Strong architectural thinking — you reason in components, ownership boundaries, and reusability before reaching for code or config.
- Experience building agentic systems and automation independently, not only assembling existing frameworks.
- Hands-on work with data at real scale — pipelines processing millions of records rather than thousands. Backgrounds in ad tech, high-load financial systems, cybersecurity / anomaly detection, or data engineering translate well.
- A strong instinct for reliability — systems that handle load and edge cases without silent failures, and a habit of validating results with control groups before trusting them.
- A research-minded approach — able to run a clean experiment and stand behind a result under scrutiny, not just ship something that mostly works.
- Comfort moving across backend, SQL, reporting, and operations.
Nice to have
- Research experience (academic or applied) where you had to defend results, not just deploy them.
- Hands-on experience with workflow orchestration tooling.
- A history of mentoring engineers technically through design and architecture discussions.
