AI Builder New Mountain View, US

Earnin; Mountain View, Northern (CA, KY); Hybrid; USD 189,000 - 231,000; Full time

Job summary

EarnIn is hiring an AI-driven software engineer who builds production-grade AI agents and tooling. You’ll work at the intersection of platform engineering, developer experience, and applied AI in Mountain View, with a hybrid in-office cadence.

The role emphasizes designing practical agent architectures and end-to-end AI workflows that ship to real users. You’ll own the entire lifecycle from design to deployment, write scalable code, and contribute to a robust evaluation and governance stack to

Qualifications

• 3+ years of full-time software engineering experience, with at least 2 years 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. We care about what you’ve built, not where you studied.
• Hands-on experience with LLM integration patterns — prompt engineering, RAG pipelines, tool/function calling, and agent architectures
• Proficiency and comfort working across the stack when needed
• 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 things other engineers actually use

Responsibilities

• Design how agents think — prompts, reasoning chains, tool calls, and the full architecture beneath them.
• Build production infrastructure for MCP servers, scaffolding, context harnesses, and a Skills Marketplace.
• Rethink the product development lifecycle to replace friction with agentic workflows.
• Own the evaluation infrastructure — pipelines, benchmarks, and quality gates for AI.
• Turn pilots into production by creating reusable libraries, templates, and reference implementations.

Skills

Software engineering

LLM integration

Across-stack proficiency

Developer experience

Agent architectures

Education

Bachelor’s/Master’s/PhD in CS/CE or related

Tools

MCP

LangChain

Open-source LLM models

Job description

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.

POSITION SUMMARY

EarnIn is making AI-native engineering a core capability — not an initiative, but how we design, build, and ship. We're not hiring a software engineer who dabbles in AI. We're hiring an AI builder who also writes great software — someone who looks at every step of how we design, build, test, and ship, and asks: why isn't an agent doing this? This is not a side project. The agents and harnesses you build here will run in production, making real decisions for real people — people who depend on EarnIn to access their pay when it matters most. If that bar excites you rather than intimidates you, keep reading.

You’ll work at the intersection of platform engineering, developer experience, and applied AI — partnering with architects, domain leads, and product engineers to build the tools, patterns, and guardrails that make AI adoption fast, safe, and durable. The Mountain View base salary range for this full-time position is $189,000 - $231,000, plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View that requires in-office work 2 days a week.

WHAT YOU'LL DO

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 take what's working and turn 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

WHAT WE'RE LOOKING FOR

• 3+ years of full-time software engineering experience, with at least 2 years 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. We care about what you’ve built, not where you studied.
• Hands-on experience with LLM integration patterns — prompt engineering, RAG pipelines, tool/function calling, and agent architectures
• Proficiency and comfort working across the stack when needed
• 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 things other engineers actually use

YOU'LL STAND OUT IF YOU HAVE

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

#LI-Hybrid

A Note on AI in the Hiring Process: EarnIn may use Artificial Intelligence (AI)-powered tools during the hiring process, including tools that (i) generate summaries or notes for interviewers, (ii) review resumes, (iii) assist with scheduling interviews, (iv) help identify themes across candidate responses and profiles for a given role, and (v) assist with populating the interview score card.

Final hiring decisions are made by human interviewers and hiring managers. If you have any questions about the use of AI in our hiring process, or would like to opt out, please connect with your recruiter. Opting out will not negatively affect your candidacy or evaluation.

At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant.

EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.