Applied AI Engineer

About this role

Azimuth already runs on AI systems the firm owns and directs: research agents, revision loops, sourcing workflows, and an internal CRM that must stay a truthful mirror of relationships rather than a busy-looking database. We need a builder who will turn that into a durable internal platform: the custom AI stack, the CRM and its integrations, and the proprietary agents the team actually uses every day.

This role will encompass product engineering for a small, high-standard firm: reliable agents, clean data contracts, human-in-the-loop review where judgment belongs to people. You will work next to the operators who live in these tools, so the bar is production usefulness.

What you will do

• Own Azimuth's internal AI platform end to end: agent runtimes, tool wiring, evaluation, logging, and the workflows that support research, harvest/revision loops, sourcing, and delivery.
• Build and evolve the firm's CRM and related systems so they stay truthful and safe for handling of confidential client context.
• Design and maintain proprietary agents the team runs in production (research, drafting under house style, ops helpers), with clear contracts, tests, and failure modes operators can trust.
• Integrate the stack with the tools the firm already uses (Google Workspace, Drive comment loops, email/calendar where authorized, Git-backed skills and docs, ATS where relevant)
• Enforce the firm's standard in software: refusal paths, source requirements, human gates on anything that could invent people or touch external systems unsafely.
• Improve reliability and operability: evals, traces, dashboards that matter, docs another engineer or power user can run, and cost/latency discipline.
• Partner with the delivery team on what to automate, what must stay human, and how new capabilities show up in real workflows rather than as unused prototypes.

What you bring

• 3 or more years building production software, with clear ownership of systems other people depended on.
• Hands-on ex...