Senior AI Builder

Mountain View · USD 228,000-279,000 · 4+ years experience · Hybrid · Posted Sep 28, 2026

At a glance

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.
We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

EarnIn is seeking a Senior AI Builder to integrate AI-native engineering into their core product development lifecycle.
The role involves building production-grade agents, evaluation infrastructure, and developer tools to enable squads to ship AI-assisted features safely and efficiently.
This position operates at the intersection of platform engineering, developer experience, and applied AI.

Design agent architectures including prompts, reasoning chains, and tool calls.
Build production infrastructure such as MCP servers, agent scaffolding, and context harnesses.
Rethink the product development lifecycle by replacing manual friction with agentic workflows.
Develop evaluation pipelines, benchmarks, and quality gates for AI systems.
Build reusable libraries, templates, and reference implementations for engineering teams.
Establish generation-to-merge and review latency baselines.
Create scaffolding for governed AI to ensure fast and safe deployment.

4+ years of full-time software engineering experience.
At least 2 years of experience building tooling, platforms, or internal developer products.
Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or a related technical discipline, or equivalent industry experience.
Hands-on experience with LLM integration patterns including prompt engineering, RAG pipelines, tool/function calling, and agent architectures.
Proficiency and comfort working across the stack.
Experience with MCP, LangChain, or comparable orchestration frameworks.
Experience with open source LLM models.
Strong opinions about developer experience and a track record of building tools for other engineers.

Hands-on experience with reinforcement learning, specifically RLHF, RLAIF, or reward modeling.
Experience in fintech or regulated/security-sensitive environments.
Hands-on work with AI governance, including bias evaluation, audit logging, and model cards.
Exposure to multi-step reasoning pipelines or human-in-the-loop system design.