Applied AI Engineer

Applied AI Engineer

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. OLarry only hires individuals based in the U.S.

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.

Benefits & Compensation

• Unlimited PTO.
• Stock Options.
• Healthcare Insurance - 100% coverage for the employee, 50% coverage for dependents.
• We are committed to investing in your career by offering continuous training and support, ensuring you acquire new skills and opportunities.

OLarry Core Pillars

• Owner Mindset: Think and spend like shareholders. Long-term, frugal, fully accountable.
• Customer-First: Start with the client, validate every idea in the market, let revenue follow.
• High-Bar Collaboration: Hire people better than ourselves and share knowledge. No silos, just collective brilliance.
• Grit & Innovation: Push through obstacles and invent better ways—experiment fast, finish strong.
• Brand Ambassadors: Grow OLarry in every interaction; selling, serving, and building trust.
• Build-to-Last: Make smart, long-term choices that compound wealth and strengthen the company; never chase quick wins.

Salary: $180,000 - $230,000 per year