[Hiring] AI Engineer @USoftware

Role Description

About the role

• Problem now:
  • Data scattered everywhere (SAP, SharePoint, HR systems)
  • No executive dashboards
  • Manual document classification (doesn't scale)
  • Briefings written by hand
• What we're building:
  • One dashboard for leadership (everything in one place)
  • AI that automatically classifies documents
  • AI that writes daily briefings
  • AI agents that do routine work
  • Proper security and governance
• What this role owns:
  • Data classification automation: implementing automated classification to remediate current failures, embedding classification into data pipelines alongside the Governance Lead
  • Operational AI agents: building production agents on top of the agentic platform — going beyond the sample agents the external partner delivers into real operational workflows
  • Agentic platform data contracts: defining what data the platform needs, in what format, with what quality guarantees — working with the Principal AI Engineer
  • AI service implementation: FastAPI service around LLM APIs with versioned prompt templates
  • Classification and briefing prompts: structured prompts returning validated JSON with tags, confidence levels, source attribution
  • Prompt versioning: templates in configuration, editable without code changes
  • Observability: every LLM call logged with input hash, model version, output, latency, token count
  • Fallback logic: graceful degradation when LLM APIs are unavailable
  • Quality evaluation: running precision/recall evaluations against human reviewer samples, reporting results, iterating prompt

Qualifications

• LLM APIs (Claude, GPT-4, open-weight models) — structured output, JSON mode, system prompts
• Prompt engineering for classification — zero-shot and few-shot
• Python — async API calls, retry logic, exponential backoff
• LLM evaluation — precision/recall, human-AI agreement scoring
• Structured output — JSON schema enforcement
• Pydantic validation - Open-weight / sovereign model APIs (Falcon, Llama, or equivalent)
• Token budgeting and context window management
• AI observability — output quality monitoring, anomaly detection
• FastAPI and Docker

Benefits

• Direct work with the customer, ownership culture.
• 20 working days of vacation and 15 sick leaves (all Ukrainian public holidays included).
• Health insurance (after trial).
• Fitness membership (after trial).
• Company legal and accounting support.
• Flexible working hours (no time trackers).
• Corporate events.