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Monarch

Software Engineer, AI (Senior/Staff)

Monarch · United States

  • Hybrid
  • Full-time
  • $150,000 / year
  • United States
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Job highlights

  • Design and build AI-driven financial features.
  • Utilize GenAI, ML, and LLM technologies.
  • Collaborate on AI architecture and infrastructure.
  • Focus on AI application layer development.
  • Drive innovation in AI for finance.

About the role

About Us

Monarch is a powerful, all-in-one personal finance platform designed to help make the complexity of finances feel simple again. Since launching in 2021, we've become the top-recommended personal finance app by users and experts. Our goal? To take the stress out of finances so our members can focus on what truly matters.

We are a team of do-ers led by experienced entrepreneurs who are passionate about helping our members reach their financial goals. We're hyper focused on building a product people love, and on finding every edge that helps us do that better. AI is core to how we operate: every person on the team uses it as a partner to sharpen judgment, move faster, and expand what's possible. We're not looking for tool mastery, we're looking for fluency and curiosity. What matters is that AI is part of how you work today and that you're actively raising your own bar on how to use it well.

As a fully remote company (even before COVID!), we welcome applicants from almost anywhere. Our team collaborates synchronously mostly from 9 AM – 2 PM PT and embraces asynchronous work to stay connected across time zones.

Join us on our mission to transform lives by simplifying money, together.

The Role

At Monarch, AI is the engine powering intelligent, personalized financial experiences for our users. We're looking for an AI Engineer to design, build, and own the features that help hundreds of thousands of users understand and manage their money.

You'll work across the full spectrum of AI development, from prompt engineering and API integrations to building multi-agent systems and fine-tuning language models. You will be a force multiplier for Monarch's product, making critical decisions on everything from our conversational AI architecture to how we evaluate and ship AI features with confidence.

You'll collaborate closely with our AI Platform team, who manage the underlying infrastructure, observability, and LLM routing. Your focus will be on the AI application layer: building intelligent features, advancing our ML systems, and ensuring quality through rigorous evaluation.

What You'll Do

  • Apply AI to Real Financial Problems: Use GenAI and ML to help users make sense of their money, whether that's understanding spending patterns, surfacing actionable insights, or automating tedious financial tasks. You'll identify where AI can make a meaningful difference and build solutions that users rely on daily.
  • Choose the Right Tool for Each Problem: Navigate the AI toolkit thoughtfully. Know when a well-crafted prompt suffices, when retrieval systems add value, and when custom models are worth the investment. You'll balance innovation with pragmatism to ship features that work reliably at scale.
  • Ship with Confidence: Leverage and enhance our sophisticated evaluation framework to ensure AI quality. You'll design test datasets, implement new scorers, and use our Braintrust-based eval system to validate changes before they reach users.

A Partnership with AI Platform

  • You Own: AI feature development, agent design and orchestration, ML model improvements, evaluation datasets and scorers, prompt engineering, and feature-level quality.
  • AI Platform Owns: LLM routing and provider management, observability and cost attribution, infrastructure reliability, and shared AI services.
  • Together You Own: End-to-end feature quality, evaluation frameworks, production incident response, and AI roadmap priorities.

What You'll Bring

  • 5+ years of experience in software engineering, with at least 2 years focused on building and operating production ML/AI systems.
  • A proven track record of shipping LLM-powered features, with deep, hands-on expertise in prompt engineering, RAG systems, and evaluation techniques.
  • Strong fundamentals in machine learning: embeddings, similarity search, classification, and probabilistic reasoning.
  • Demonstrated experience building and using AI evaluation tooling (e.g., golden sets, rubric scoring, LLM-as-judge).
  • Excellent Python skills and a history of building production-grade AI features and services.
  • Strong collaboration and communication skills with a sharp product sensibility.
  • A strategic mindset, comfortable making build-vs-buy decisions and designing features for long-term reliability.

Nice To Haves

  • Multi-Agent Systems: Designing and building complex LLM orchestration with frameworks like LangGraph, CrewAI, or AutoGen.
  • Fine-Tuning: Hands-on experience with LoRA, RLHF, or full fine-tuning on platforms like Vertex AI.
  • Fintech Domain: Background in personal finance, banking, or data-rich consumer financial applications.
  • Vector Databases: Hands-on experience with OpenSearch, pgvector, Pinecone, or similar at scale.
  • Safety & Evaluation: Experience with red-teaming exercises, adversarial testing, and implementing guardrails.

Typical Process

  • Recruiter Video Call
  • Hiring Manager Video Call
  • Technical Assessment (Live Coding)
  • Virtual Onsite consisting of 3 rounds
  • Reference Checks
  • Offer

Benefits

  • Work wherever you want! As a fully remote company with no central office, we want you to work wherever you are happiest and most productive. Whether that’s out of your home, a co-working space, or elsewhere.
  • Competitive cash and equity compensation in a hyper growth, early stage company 🚀.
  • Stipend to set-up your ideal working environment.
  • Competitive Benefit Plans for employees based on your location (e.g. in the US we offer: Medical, dental and vision benefits and the ability to contribute to a 401k plan).
  • Unlimited PTO.
  • 3 day weekend every month! We take off the “First Friday” every month to focus on rest, recuperation, or just having fun!

Equal Opportunity & Non-Discrimination

We are an equal opportunity employer and value diversity. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy and gender identity), sexual orientation, age, marital status, veteran status, disability status, or genetic information.

Applicant Notices

California & San Francisco: Pursuant to the California Fair Chance Act and the San Francisco Fair Chance Ordinance, qualified applicants with arrest and conviction records will be considered for employment. We comply with all applicable fair chance hiring laws.

Key skills/competency

  • AI Engineering
  • Software Engineering
  • Prompt Engineering
  • RAG Systems
  • Machine Learning
  • LLM
  • Python
  • Feature Development
  • ML Models
  • Evaluation Frameworks

Skills & topics

  • AI Engineer
  • Software Engineer
  • Prompt Engineering
  • RAG
  • Machine Learning
  • LLM
  • Python
  • Fintech
  • Remote
  • Generative AI

How to get hired

  • Tailor your resume: Highlight your 5+ years of software engineering experience and 2+ years in production ML/AI systems. Emphasize your LLM feature shipping, prompt engineering, RAG, and evaluation expertise.
  • Showcase AI fluency: Demonstrate your curiosity and hands-on experience with AI tools, especially in your Python projects. Mention any experience with multi-agent systems or fine-tuning.
  • Prepare for technical assessment: Be ready for live coding exercises focusing on Python and AI/ML concepts. Practice building production-grade AI features and services.
  • Understand the process: Familiarize yourself with the typical hiring stages: Recruiter Call, Hiring Manager Call, Technical Assessment, Virtual Onsite, and Reference Checks.
  • Highlight remote work skills: Emphasize your ability to collaborate effectively in a fully remote, asynchronous environment, particularly your communication and product sensibility.

Technical preparation

Practice Python coding for AI applications.,Build and evaluate RAG systems.,Design prompts for financial LLMs.,Implement ML fundamentals in code.

Behavioral questions

Describe a complex AI problem you solved.,How do you collaborate with AI platform teams?,Explain your decision-making on build vs. buy.,How do you ensure AI feature quality?

Frequently asked questions

What is the work arrangement for the Senior/Staff AI Software Engineer role at Monarch?
This is a fully remote position at Monarch. The company has no central office, allowing employees to work from wherever they are most productive. Collaboration primarily occurs synchronously from 9 AM – 2 PM PT, with asynchronous work embraced to connect across time zones.
What are the key responsibilities for an AI Engineer at Monarch?
As an AI Engineer at Monarch, you will design, build, and own AI-powered features for the personal finance platform. This includes prompt engineering, API integrations, building multi-agent systems, fine-tuning language models, and defining conversational AI architecture. You will also work on advancing ML systems and ensuring quality through rigorous evaluation.
What qualifications are essential for the Senior/Staff AI Software Engineer position?
Essential qualifications include 5+ years of software engineering experience, with at least 2 years focused on production ML/AI systems. Proven experience shipping LLM-powered features, deep expertise in prompt engineering, RAG systems, and evaluation techniques, strong ML fundamentals, and excellent Python skills are required.
Does Monarch offer benefits to its remote employees?
Yes, Monarch offers competitive benefits. These include competitive cash and equity compensation, a stipend for your ideal working environment, and competitive benefit plans based on location (e.g., US employees receive medical, dental, vision, and 401k contribution options). They also offer unlimited PTO and a monthly 3-day weekend.
What kind of AI projects will I be working on at Monarch?
You will apply AI to real financial problems, helping users understand their money through spending pattern analysis, actionable insights, and task automation. This involves choosing the right AI tools, from prompt engineering and retrieval systems to custom models, and shipping reliable features at scale.
What is Monarch's approach to AI development and collaboration?
Monarch views AI as a core operational component. AI Engineers work on the AI application layer, building features and advancing ML systems. They partner closely with the AI Platform team, who manage infrastructure, LLM routing, and observability. Together, they own end-to-end feature quality and the AI roadmap.
How does Monarch ensure the quality of its AI features?
Monarch leverages and enhances a sophisticated evaluation framework. This includes designing test datasets, implementing new scorers, and using a Braintrust-based evaluation system to validate changes before they reach users. Rigorous evaluation is a key part of shipping with confidence.
What is the typical hiring process for an AI Engineer at Monarch?
The typical hiring process includes a Recruiter Video Call, a Hiring Manager Video Call, a Technical Assessment (Live Coding), a Virtual Onsite interview (consisting of 3 rounds), Reference Checks, and finally, an Offer.