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Built's Mission: Connect and simplify doing business in real estate.
Built is the AI-powered platform transforming the way real estate is financed, developed, and managed. Purpose-built for real estate and construction, Built began by fixing construction draw management for lenders and has grown into a comprehensive operating system addressing some of the industry’s most complex challenges. Today, Built is a partner to more than 350 lenders, over 80,000 borrowers and owners, and thousands of contractors, powering 86,000 active projects valued at more than $300 billion. Learn more at getbuilt.com .
Built is the AI-first platform for construction and real estate finance, managing over $300 billion in annual capital for more than 340 lenders — including 45 of the top 100 U.S. banks. The software Built engineers build governs how capital moves through construction projects: the AI Draw Agent that automates construction loan draw management for institutions like Fifth Third and Ameris, the lender portfolio risk tools that give banks real-time visibility into construction exposure, the compliance and document workflows that protect both borrowers and financial institutions, and the APIs that connect Built to core banking systems across the country. In a domain where precision, reliability, and performance have direct financial consequences, the engineering bar at Built is correspondingly high.
This role sits on Marketplace, expanding Built beyond workflow software into the services that surround every construction project, like inspections, appraisals, insurance, and materials sourcing. The team moves fast: standing up new products with real customers, building the durable platform underneath them, and sharpening the ones already in market.
As a Staff Innovation Engineer , you'll flex across all three of those - architecting core systems, taking new product ideas from concept to pilot, and improving products already in the hands of customers. This is a hands-on building role, not a people-management one, though at the staff level you're expected to drive system design on major initiatives and mentor other engineers on the team.
Our Guiding Principles
Be Bold. We pursue the biggest problems in our industry, challenge assumptions others take for granted, and take calculated risks to get there. We don't hide behind consensus or committees. Playing it safe is just failing slowly.
Help Customers Win. We learn our customers' businesses deeply — how they think, how they deploy capital, what keeps them up at night. We treat their capital like our own. We ship leverage, not features. And we measure ourselves by customer results, not our intentions.
Move with Urgency & Purpose. We bias toward delivery over perfection, remove friction from our own paths, and communicate in real time. Momentum compounds — and we build it every day.
Own the Outcome. We own outcomes, not just tasks. We hold a high Say:Do ratio and take responsibility from idea through impact. When something breaks, we fix it — we don't wait to be asked.
Never Satisfied. We raise the bar continuously. We stay curious, hold exacting standards, debate hard, and hold our opinions loosely when the evidence shifts. Excellence is a habit, not an event.
The Team
Marketplace is a tight-knit, tenured team that recently became its own business unit at Built. It's a collaborative group with a strong culture of mentorship and code review.
What You'll Do
Platform & primitives: Design and build the durable, reusable services that every Marketplace product depends on — things like purchase orders, contract terms, invoicing rails, and workflow/status state machines — using fine-grained microservices and asynchronous workflow orchestration (e.g., Temporal). This work is judged on quality attributes: maintainability, scalability, reliability, and flexibility.
New product bets: Partner directly with customers to scope a problem, ship a working (not perfect) version of a new marketplace product within about 30 days, and iterate weekly based on direct customer feedback. Form and test hypotheses with discipline — know when to keep pushing, when to pivot, and when to walk away.
Adoption & optimization: For products that have already launched, focus on quality, craftsmanship, and driving adoption and usage — optimizing workflows and click paths and making the product the best version of itself for customers already using it.
AI-native development: Build and refine agent harnesses and layered prompting systems (system, policy, and steering prompts) that automate real workflows — for example, extracting and reasoning over unstructured documents (loan covenants, plans and specs, appraisals) using a mix of AWS Textract, GCP Document AI, and direct calls to models like Claude, Gemini, and OpenAI, choosing the right tool for the document and cost profile. Build and use internal eval tooling to test and improve these systems before and after they ship.
Partner with product, design, sales, and the General Manager to understand customer problems and give input on pricing, GTM, and scale/pivot/kill calls for the bets you're closest to — final commercial decisions rest with the GM and PM, not the engineer.
Mentor other engineers on the team through code review and pairing, and contribute to system design and architecture decisions even on bets you aren't personally driving.
Maintain the team's service and product-API boundaries (services don't call services; product APIs stay one-to-one with the user journeys they serve) as the team scales its footprint.
What You'll Bring
7+ years of experience in software engineering, with strong backend/distributed-systems fundamentals — designing services and APIs that need to be reliable and maintainable, not just prototypes.
Hands-on experience building and shipping 0-to-1 products or features in a fast-iteration environment with real customers, ideally using design-partner or similar validation approaches.
Experience building with or integrating multiple LLM providers (e.g., Claude, Gemini, OpenAI) and document-extraction tooling (e.g., AWS Textract, GCP Document AI), including knowing when to fall back from a structured extraction tool to an LLM.
Experience building agent harnesses, RAG pipelines, or other AI/LLM-integrated workflows, along with the evals or testing practices needed to trust and improve them.
Data engineering, ML, or heavy document-processing background is a strong plus — a meaningful share of this team's work is reasoning over unstructured, non-standardized documents (legal terms, covenants, inspection reports).
Comfort working across the stack as needed — this is a full-stack-capable engineering role, not a narrowly scoped frontend or backend specialization — plus genuine curiosity about the customer problem, low ego, and a preference for working closely with product rather than in a handoff model.
Experience in financial services, construction, real estate, payments, lending, insurance, or other complex B2B environments is a meaningful differentiator, though not required.
What Success Looks Like at Six Months
You've made a substantial, visible contribution in at least one of the team's three workstreams — a platform primitive that other bets now build on, a new product taken from hypothesis to a validated pilot with real customers, or a measurable adoption/usage improvement on a live product.
You've built or meaningfully improved at least one agent-driven or AI-integrated system that's in production use.
Engineers and cross-functional partners on the team would describe you as a strong collaborator who raises the bar on system design and is genuinely curious about the customer problem, not just the code.
If you mentored the team's newer engineer(s), they're visibly applying stronger patterns in their own work.
AI & Technology Expectations
Leverage AI tools to enhance the productivity, quality, and speed of your work.
Use AI to support drafting, analysis, summarization, and problem-solving across your role.
Identify opportunities to streamline workflows and reduce manual effort through automation and AI.
Apply AI to sharpen decision-making and strengthen technical and product insights.
Share effective AI use cases and best practices with your team.
Built’s salary range for this position is $180,000-$240,000 USD per year. The pay range is designed to accommodate upward mobility in the role; therefore, it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees; your total rewards package at Built will include equity, market-current medical, dental and vision coverage, an unlimited PTO policy, and other benefits.
Travel Requirement: Employees who are not based in the Nashville area are required to travel to our Nashville office at least twice per year for company gatherings, such as Connect Week. Additional travel to Nashville may be required based on your role and business needs.
Perks:
The rare opportunity to radically disrupt a $1.5T industry
Robust compensation package, including equity in the form of stock options
Learning Grant program to support ongoing professional development
401k with match and expedited vesting [US ONLY]
Built brings together passionate people who are driven in a variety of disciplines, each bringing their unique perspective to everything they do. We’re committed to building a safe, inclusive workplace where every employee can succeed, and we recruit, hire, and promote fairly - without bias based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, veteran status, disability, genetic information, or any other characteristic protected by law.
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