Job Title: Applied AI Engineer
Location: Remote, U.S. Only
Use your skills to craft the next generation of Tax practice.
About Us
OLarry is shaping the future of tax by bringing together tax experts and technology leaders to create a tax practice that provides exceptional service supported by leading proprietary technology. We want to help HENRY’s (High Earner Not Rich Yet) and beyond build better relationships with their accountants to guide wealth across generations.
About the Role
As an Applied AI Engineer, you will be instrumental in defining OLarry’s growth by defining, planning, and implementing our tax preparation and planning solutions. This role reports to the COO.
Responsibilities
- Ensure the timely and high-quality delivery of engineering projects by setting clear priorities and deadlines.
- Build a pipeline that takes messy PDFs or scanned tax docs and extracts structured, searchable data — even when the AI gets it half-right
- Fine-tune how we use AI and vector search to automatically classify uploaded documents into categories like “Filed Return” or “Supporting Doc”
- Create a confidence scoring system for LLM outputs so downstream services know when to trust the data, and when to loop in a human.
- Prototype an AI-driven “Tax Scenario Planner” where users can explore what happens to their taxes if they sell stock, start a side business, or move states.
- Build a module that looks at a customer’s past return data and suggests tax-saving opportunities or gaps, using both rules and AI inference.
- Implement a forecasting tool that simulates future tax outcomes based on different income streams and entity structures.
- Help design a system that asks smart follow-up questions to refine a scenario, like an AI-powered tax assistant.
- Build LLM-powered summarization tools that explain complex return data to non-experts in plain language.
- Create internal tools for financial advisors or CPAs to visualize multiple return scenarios side-by-side for their clients.
- Explore collaborative filtering approaches to recommend planning strategies based on what similar users have done, without breaching data privacy.
Skills & Experience
- You’ve built and shipped real-world AI features — especially ones involving documents, workflows, or user-facing automation.
- You’re comfortable working with large language models (LLMs) and know how to make them useful, whether that’s through prompt design, retrieval-augmented generation (RAG), or smart fallback logic when things go sideways, multi-agent pipelines.
- You’ve worked with vector databases, semantic search, or memory-like systems, and have opinions about how to make them fast and relevant
- You think in systems — how to break down complex, fuzzy tasks (like reading a tax form) into repeatable, reliable steps
- You’re hands-on with Python and comfortable owning ML pipelines end-to-end, from prototype to production
- You’ve worked with both structured (relational tables) and unstructured data (PDFs, forms, notes), and know how to stitch them together in a useful way
- You care about the user experience, not just the model output, and like working closely with product and design
- Previous experience with fintech or similarly regulated space
- A high level of EQ, personal drive, and professionalism that adheres to the OLarry Core Pillars.
Bonus if you’ve built tools or workflows involving:
- Scenario modeling or forecasting (e.g., helping users explore “what-if” outcomes)
- Recommendation systems (especially collaborative filtering or ranking systems)
- Multi-agent coordination or building agents that can reason through complex tasks
Benefits & Compensation
- Unlimited PTO.
- Stock Options.
- Healthcare Insurance - 100% coverage for the employee, 50% coverage for dependents.
- Generous revenue sharing for all new business development.
- We are committed to investing in your career by offering continuous training and support, ensuring you acquire new skills and opportunities.
We are committed to creating a diverse and inclusive workplace. We do not discriminate based on race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws. We are also committed to complying with the Ban the Box legislation, which prohibits employers from inquiring about an applicant's criminal background history until a conditional job offer has been made.
OLarry Core Pillars
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Personal Ownership: All team members of both the company and acquired CPAs will own a stake in the company. With this equity, an expectation of acting as an owner of their given area is expected.
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Demonstrate Grit: All successful new ventures take time and determination. Team members are expected to be personally driven to succeed on the schedule required by the work and to put their short-term financial needs behind the company's long-term needs.
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Collaboration Before Siloed Heros: The strongest products are built by many minds with many viewpoints, not individuals. All team members must hold themselves to a high level of communication and cross-collaboration. No projects or products should be produced in a silo.
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Work Backwards: Everything we do puts the customer at the heart. If the customer is happy, the revenue will come.
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Market Validation: All products and processes should be tested and validated with the target customer before any major commitment to the project commences. All team members are responsible for talking to customers and understanding their needs.
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Area Expertise: Each team member will be the given expert in their allotted part of any project, and knowledge will be deferred to as such.
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Build the Brand: Every team member will be responsible for building the OLarry brand through social, sales, or customer support.
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Long-term View with a Global Focus: Strategic decisions will be made with a company's first view for building long-term wealth globally before short-term personal gains or expenses.
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Think Bootstrapped, not Funded: Team members will treat OLarry’s cash like their own, being careful only to spend it when a valid business case is presented and no market short—or long-term alternative is available.