Senior Software Engineer (AI/Data)

<p style="min-height:1.5em"><strong>About Codat</strong></p><p style="min-height:1.5em">Codat is an advisory intelligence solution purpose-built for modern commercial banking. Through rich, specialized data, forward-looking insights, and integrated workflows, Codat empowers banking teams to deepen their relationships, grow their revenue, and simplify their day-to-day work.</p><p style="min-height:1.5em">Founded in 2017 and backed by JPMorgan, PayPal, Amex, Plaid, and Shopify, Codat has successfully powered over 350,000 connections to business customers’ financial systems — and is trusted by industry leaders to turn scattered information into actionable, strategic advantages in real time, every time.</p><h2><strong>The Role</strong></h2><p style="min-height:1.5em">We're building the Advisory Intelligence Platform: Codat's client intelligence delivered inside the assistant a banker already uses (Microsoft Copilot first). Ask it anything about a client and it answers from the client's real books. Don't ask, and it still tells you what's changed, why it matters and what to do about it. Under it we're building the semantic layer, so every answer uses the same definitions, the signal layer that spots what's changed for a client, and the reasoning layer, a Codat-side LLM that turns those signals into advice. The first bank goes live this year. You'll be building the data and reasoning behind all of it.</p><p style="min-height:1.5em">This is a hands-on job for software engineers who want to build the systems a model reasons over, not configure a warehouse. Codat is AI-first, not AI bolted onto SaaS. The product lives inside the AI assistant our clients already use, and we build it the same way: agents do the repetitive work, engineers do the hard parts. You'll build it and you'll run it. Nobody hands it over the wall once it's live. You'll also get a real say in where it goes next. That means making your case to engineers, product and the commercial team, and bringing them along with you.</p><p style="min-height:1.5em"></p><h2><strong>What You'll Work On</strong></h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">The semantic layer. Measures, dimensions and definitions the model is allowed to use, so every answer it gives is the same answer. Yours to grow, persona by persona.</p></li><li><p style="min-height:1.5em">The signal layer. Detecting what's changed for a client and surfacing it before the banker asks. You'll be designing and building this.</p></li><li><p style="min-height:1.5em">The reasoning layer. A Codat-side LLM that turns signals into advice. Our calculations are the ground truth it reasons over. You own the calculations the model relies on, and the names, definitions and structure that let it pick the right one.</p></li><li><p style="min-height:1.5em">The agents and MCP (Model Context Protocol) servers behind the assistant. What tools it has, how they're built, how they fail, and the evals that prove they work.</p></li><li><p style="min-height:1.5em">Everything from raw source data to the number the assistant quotes: the pipelines, services and data models, with the testing and observability to prove the number is right and the evals that catch the model quoting the wrong one.</p></li></ul><h2><strong>You'll Probably Have</strong></h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Built production systems from scratch, writing the code yourself rather than configuring managed services. You think about interfaces, failure modes and how the next person will