Design and document principled architectures, balancing deterministic logic, ML, and LLMs.
Build scalable, reliable workflows across no-code and custom services.
Implement explainable, traceable allocation and matching systems with human-in-the-loop escalation.
Own schemas, pipelines, and integrations across SaaS systems.
Develop CRMs, dashboards, and operational tools using low-code and framework code.
Implement approval systems, audit trails, and compliance-ready event logs.
Deliver automated reporting, structured logs, metrics, and monitoring.
Ship production-ready LLM features with evaluation harnesses and cost/latency optimization.
Own production reliability, incident response, and enforce strict access controls.
Lead projects end-to-end — discovery, design, build, rollout, training, and optimization.

5+ years in software or automation engineering, with 2+ years building production AI/LLM-backed systems.
Strong coding skills in Python and/or TypeScript/Node.js (both preferred).
Advanced SQL skills for complex queries and performance optimization.
Experience with workflow tools (Make.com, n8n, Zapier) and backend fundamentals (REST APIs, queues, retries).
Data warehousing expertise (BigQuery or equivalent).
Integration experience with SaaS platforms (e.g., Asana, Zoho, Slack, Google Workspace).
Track record of owning production systems end-to-end (e.g., allocation engines, workflow platforms, CRMs, data warehouses).
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
English proficiency (CEFR C1 or above).

AI Systems – Automation Engineer

Key skills