About this role
EarnIn develops products that provide real-time financial flexibility and earned wage access for people living paycheck to paycheck. This team integrates AI-native engineering as a core capability across design, build, test, and ship workflows, moving beyond simple feature experiments to robust production systems.
The senior engineer joining this group focuses on the intersection of platform engineering, developer experience, and applied artificial intelligence. Responsibilities include building production-grade agents, modernizing the product development lifecycle with agentic workflows, and establishing evaluation pipelines that guarantee safety and performance.
Ideal candidates bring a blend of strong software engineering foundations and hands-on LLM integration expertise. A successful person in this position relishes the challenge of creating internal tools and governance frameworks that other engineering squads rely on daily.
What you will do
- Design and build production agents incorporating prompts, reasoning chains, tool calls, and underlying architectures like MCP servers and context harnesses.
- Rethink the product development lifecycle by replacing manual friction with automated agentic workflows for scoping, testing, deployment, and monitoring.
- Own and scale evaluation infrastructure, building pipelines, benchmarks, and quality gates to monitor model performance and reliability.
- Transform successful engineering pilots into reusable libraries, templates, and reference implementations that other squads can rapidly fork and deploy.
- Partner closely with architects, domain leads, and product engineers to establish guardrails that make artificial intelligence adoption fast, safe, and durable.
- Define and track generation-to-merge metrics and review latency baselines to ensure model quality remains visible and trustworthy across teams.
What you need
- Four or more years of full-time software engineering experience.
- At least two years of experience building tooling, platforms, or internal developer products.
- A degree 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 calling, and agent architectures.
- Proficiency and comfort working across the full software stack when needed.
- Experience working with MCP, LangChain, or comparable orchestration frameworks.
- Familiarity with open source large language models and strong opinions about developer experience.
Nice to have
- Hands-on experience with reinforcement learning, especially RLHF, RLAIF, or reward modeling in applied product contexts
- Experience in fintech or regulated and security-sensitive environments
- Hands-on work with AI governance such as bias evaluation, audit logging, and model cards
- Exposure to multi-step reasoning pipelines or human-in-the-loop system design
Benefits
- Equity
- Benefits
Skills and tech stack
Questions candidates ask
What is the location and remote work policy?
This is a hybrid position in Mountain View that requires in-office work 2 days a week.
What is the salary range for this role?
The Mountain View base salary range for this full-time position is $228,000 - $279,000, plus equity and benefits. Salary ranges are determined by role, level, and location.
What kind of experience is required for this position?
Candidates need 4+ years of full-time software engineering experience, with at least 2 years building tooling, platforms, or internal developer products. Hands-on experience with LLM integration patterns is also required.