Agents that take real actions. You'll design how agents think — prompts, reasoning chains, tool calls, and the full architecture beneath them. From MCP servers and agent scaffolding to context harnesses and a Skills Marketplace, you're building the layer every squad at EarnIn builds on. Not a proof of concept. Production infrastructure.

A PDLC that doesn't look like 2022. The product development lifecycle is overdue for a rethink. You'll challenge each stage — from scoping and design through to review, testing, deployment, and monitoring — and replace manual friction with agentic workflows wherever it makes sense. Evaluation pipelines, automated PR hygiene, deployment gating, generation-to-merge metrics: you'll build the scaffolding that makes governed AI fast, not slow.

Evals that actually mean something. You'll own the evaluation infrastructure — building the pipelines, benchmarks, and quality gates that tell us whether our AI is working, degrading, or ready to ship. That means designing eval harnesses for AI-assisted workflows, setting generation-to-merge and review latency baselines, and making model quality visible and trustworthy across teams. If you've built evals that caught real problems before they hit production, you'll fit right in.

Pilots that graduate to production. EarnIn's engineering leads are running experiments. You'll be the person who takes what's working and turns it into something the next team can fork and ship in a week. Less "interesting prototype," more "thing we rely on." You’ll build reusable libraries, templates, and reference implementations that give squads a running start on AI integration, so no one has to solve the same problem twice

WHAT SUCCESS LOOKS LIKE

Teams across engineering can ship AI-assisted features faster, with fewer rework loops

The harnesses you build are actively used and well-documented

AI pilot quality and safety metrics are visible, trustworthy, and improving

Senior AI Builder

Responsibilities

Qualification

Required

Benefits

Company

Earnin

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