Senior Software Engineer - AI Agents (Python)

Responsibilities

• Own the production agent fleet day to day — reliability, monitoring, incident triage, and continuous improvement of agents colleagues rely on every morning. When an agent misbehaves, you are the person who understands why.
• Build new agents and capabilities on the company’s standard open-source agent framework, from business conversation to production: scoping with the stakeholders who will use them, prompt and tool design, deployment, and hand-off into an owned-and-evaluated agent registry.
• Build the evaluation discipline — regression evals, output-quality scoring, per-agent cost tracking, and failure-mode analysis, so “the agent got better” is a measured claim, not an impression.
• Integrate the agent memory layer — a self-hosted open-source memory service that lets agents retain, recall, and reflect — honoring the platform’s one-way lineage rule: facts flow from the BigQuery warehouse into agent memory, never the reverse.
• Migrate existing agents onto the company-run cloud runtime without breaking the live Slack workflows their users depend on — a careful, one-agent-at-a-time program with a defined order.
• Do the integration engineering agents depend on — LLM APIs, MCP integrations, Shopify and marketing/analytics APIs, and clean handoffs to deterministic workflow automation (n8n) — with the judgment to know what should be agentic, what should be deterministic, and what must stay human.
• Implement governance in code — permissions, approval gates, and human-in-the-loop routing, including flows where content is compliance-sensitive and human approval is not optional.
• Work AI-assisted — the team already adopted Claude Code and Cursor on its own initiative; you work that way too and help raise the shared standard.

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