Staff Software Engineer, Data – AI

🕒 May 26

🏈 Alabama, Alaska, +43 more states – Remote

🏈 Alabama – Remote 🐻 Alaska – Remote 🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🐊 Florida – Remote 🌺 Hawaii – Remote 🥔 Idaho – Remote 🌽 Illinois – Remote 🌾 Iowa – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote 🦞 Maine – Remote 🦬 Montana – Remote 🌾 Nebraska – Remote 🎰 Nevada – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🌶️ New Mexico – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🌾 North Dakota – Remote 🏈 Ohio – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote ❄️ Minnesota – Remote 🎸 Mississippi – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🌴 South Carolina – Remote 🗿 South Dakota – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote ⛰️ West Virginia – Remote 🧀 Wisconsin – Remote 🦬 Wyoming – Remote

💵 $210k - $260k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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Juniper Square

WebsiteLinkedInAll Job Openings

201 - 500 employees

💸 Finance

🏠 Real Estate

☁️ SaaS

💰 $75M Series C on 2019-11

Finance • Real Estate • SaaS

Juniper Square is a company that provides a comprehensive platform and solutions tailored for private investment partnerships. Founded in 2014, the company focuses on enabling seamless connection and communication between General Partners (GPs) and Limited Partners (LPs) throughout the entire investment lifecycle. Juniper Square's technology is purpose-built to support commercial real estate, private equity, and venture capital firms of all sizes. The platform offers services such as fund administration, fundraising, investor management, compliance, and investor reporting, all aimed at enhancing transparency, data governance, and the overall investor experience.

📋 Description

• Design and ship the data normalization, schema mapping, validation, enrichment, and distribution pipeline for a net-new intelligent data warehouse • Write production code as a hands-on individual contributor - this is not a role that delegates implementation to others • Take technical ownership from architecture through deployment, with accountability for reliability, performance, and correctness • Partner with a small seed team to define the end-to-end architecture for an AI-native data warehouse serving institutional financial clients • Bring opinionated decisions on schema design, normalization strategies, API exposure patterns, and data distribution approaches • Evaluate and select technologies with a bias toward what ships well and scales sustainably • Design and implement the evaluation framework that makes AI-generated outputs trustworthy in high-stakes financial data contexts • Build cross-model comparison tooling, deterministic validation checks, and human-in-the-loop review workflows • Contribute to shared AI evaluation infrastructure that can serve as a foundation across multiple products • Use agentic coding tools and LLM-assisted development as your primary workflow - this is how the entire team operates • Bring strong opinions about how to get the most from AI-assisted development while maintaining quality and reliability • Set coding standards, review practices, and architectural documentation that will scale as the team grows • Help define what "good" looks like for a team building at speed without sacrificing quality • Mentor engineers and provide technical guidance as the team expands

🎯 Requirements

• 7+ years of software engineering experience, with demonstrated Staff-level technical scope and impact • A portfolio of shipped production systems - we will ask you to walk through specific technical decisions you personally made and code you personally wrote; this is not a role for someone whose primary contribution has been directing others • Strong hands-on experience with data pipeline or data warehouse engineering: schema design, ETL/ELT patterns, normalization, and API-based data distribution • Production experience building with LLMs: prompt design, model orchestration, evaluation, and output validation in real systems, not just experimentation • Fluency with AI-assisted and agentic development workflows; you use these tools daily and have strong opinions about how to use them effectively • Experience with AWS data infrastructure; Redshift experience a plus • Strong written communication —- able to translate technical design into clear documentation for both engineering and product audiences • Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases.

🏖️ Benefits

• Health, dental, and vision care for you and your family • Life insurance • Mental wellness coverage • Fertility and growing family support • Flex Time Off in addition to company-paid holidays • Paid family leave, medical leave, and bereavement leave policies • Retirement saving plans • Allowance to customize your work and technology setup at home • Annual professional development stipend