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Ying Wang, Owner of Paint Creek Software

Ying Wang, Owner
Software engineer, 2× founder/CTO, and investor

Tailored specifications. Lightning delivery.

Full-service software delivery, from written spec to production, with a software factory behind it.

In their words

What managers, direct reports, and clients say about working with Ying.

  • Ying joined our data platform work for a federal health agency before the requirements were nailed down, and he quickly started contributing and helping shape the product and architecture. He advised on how to architect the data producer and consumer model and built the full system working end to end. The results we delivered to the client were way beyond expectations and highly praised. I look forward to working with Ying in the future on many more highly-technical projects.
    Allan CarrollManaging Partner & CTO at StrataEdge; more than $100M raised
  • Initially, I had concerns about our acquisition channel reporting pipeline, which had been experiencing frequent downtime. This hindered our ability to effectively measure, improve, and scale our acquisition channels. However, Ying stepped in and implemented measures to strengthen the pipelines, thereby ensuring that the business could depend on accurate and timely acquisition channel data. I was particularly impressed by the level of engagement that Ying brought to the project, collaborating with stakeholders to ensure that their needs were met. Ying's ability to work seamlessly across functions and effectively apply technology to solve complex business issues is a testament to his exceptional engineering skills.
    Mike Spainhowerfmr. CTO, Caribou
  • Ying is an incredible talent. The first time we met in Q3 2023, I had mentioned a few things about the mortgage industry, and how consumers had limited access to understanding a certain topic. Within 3 days, he had a working OpenAI ChatGPT persona trained and running on a site that blew me away. He has an entrepreneurial spirit, strong work ethic, and a desire to continue learning which is a fantastic recipe for success.
    Mike Eshelmanfmr. CMO, Mr. Cooper (acq. Rocket Mortgage)
  • You want the data engineering job done right? You want Ying. He is the consummate professional who seeks to understand his customer's needs and then implement innovative solutions. What I really enjoyed about working with Ying is that I knew I could provide some high-level requirements and step away to focus on other items. He always delivered for me and my teams.
    Alan McKellarfmr. VP of Engineering, Janus Health
  • I had the pleasure of working with Ying on a cutting-edge proof of concept in a space where success criteria were still being defined. That kind of ambiguity is hard to navigate, and Ying handled it exceptionally well, thinking creatively, partnering closely with product management, and helping the team stay aligned on quality outcomes. What stood out most was how much pride Ying took in the work, both his own and the team's. He's easy to collaborate with, tireless in pushing projects toward success, and has a genuine knack for seeing how all the pieces of a solution fit together. His skillset is exactly what today's AI/ML landscape demands, and any team would be fortunate to work with him.
    Stacy Stonich, MBA, CISSP, PMPExecutive Technology Leader, AI Governance
  • Ying is a strong innovative engineer with a high work ethic. His expertise in data engineering and data architecture will be a benefit to anyone working with him.
    Linda ApsleyManaging Partner at StrataEdge; former CTO at GEICO
  • The reason this [project] was one of the more seamless integrations I’ve worked on is because of good attitudes from you and others and the willingness to come back to the table over and over again and clarify things through dialogue. A lot of companies never make it this far, they're stuck with [legacy solutions].
    VP of Acquisition MarketingSeries F security startup
  • As a former direct report to Ying, I am extremely grateful for the opportunity to have worked with him. Ying is laser-focused on delivering high-quality results for the business while also understanding the importance of seeing people as people. He genuinely cares about the well-being of his team and is a strong champion of both their professional and personal growth. I can say wholeheartedly that I would not be the engineer I am today without his guidance.
    Lihan ZhangSoftware Engineer
  • Ying was the senior engineer and leader of the Data Engineering team at Caribou when I joined and both the company and I benefitted greatly from his technical knowledge, leadership skills, and friendly personality. Ying was instrumental in my growth as an engineer and challenged me to improve while also being fully supportive. His knowledge of software and data engineering is both broad and deep. Each project Ying led came in on time and with resounding success. I give my highest possible recommendation for Ying as both an engineer, leader, and friend.
    Addison JonesSoftware Engineer
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Ying Wang, Owner of Paint Creek Software

Who you work with

Ying Wang, Owner

Software engineer, 2× founder/CTO, and investor

Software engineer, 2× founder/CTO, and investor. Before Paint Creek: Xometry's AI/ML pricing and win rate engine, Caribou's data engineering team, and two mortgagetech startups as CTO, where he shipped a digital mortgage application and an AI assistant for down-payment assistance. Now he builds and runs the software factory that delivers every engagement.

On a client project, Ying writes the spec, approves every merge, and is the person on the weekly pulse check.

From the record

Team grown at Caribou
1 to 10
The data engineering team he founded, seven full-time and three contractors, from Series A to a $1.1B Series C post-money valuation.
Xometry's IPO (NASDAQ: XMTR)
$2B
Three years after his four-person team platformed the company's first AI/ML pricing and win rate engine. Its 2021 annual report: “we price transactions through our proprietary, AI-enabled instant quoting engine.”
Data warehouse refresh performance at Caribou
36×
Faster: from six hours to ten minutes.
Cloud spend cut at Caribou
$10K
A month, a $120K annual run rate, from incremental refresh and partitioning of the data lakehouse.
Lifetime raised as a startup CTO
$550K

How a pilot engagement runs: two-week cycles

Each cycle audits, plans, builds, reconciles and delivers; the next one starts from what production said. You own the repository from the first cycle.

  1. 1Day 1

    Audit

    We read the code, the backlog and the numbers you care about, and write down what is actually there: architecture, risks, test coverage, and what is blocking delivery. Later cycles audit what the last one shipped.

  2. 2Day 1

    Plan

    The audit becomes the cycle's written spec: acceptance criteria, the tasks that fit in the rest of the cycle, and the cost. You approve it before any code is written.

  3. 3Days 2 to 5

    Implement

    Built through the factory, in your repository: you watch the pull requests land as they happen.

  4. 4Days 5 to 9

    Reconcile

    The ledger for the cycle: what shipped against the spec, what it cost, and what changed. Plans change, especially at an early-stage company, and that is expected; the reconcile is where a change gets written down and re-estimated the week it happens, so the spec stays true and nothing surprises anyone at the end.

  5. 5Day 10

    Deliver

    Release to production through CI/CD, with monitoring and documentation in place. What production says becomes the first input to the next cycle's audit.

What we build for clients

  • Product Engineering

    Greenfield web apps, APIs and infrastructure, built from spec to production. For a new product that means scoping the thin slice, building it through the factory and launching it to real users in weeks; for an existing one, the next features on the same footing.

  • Data Ecosystem Development

    Data ecosystem development for regulated environments like finance, healthcare, and government: ingestion, warehouses and lakehouses, attribution and reporting, and the reliability and audit trail that regulated data needs.

  • Prototype to Production

    Porting an application built on Lovable, v0, Base44 or Replit to a production-grade system when it starts to scale: a real data model, auth, tests, deployment and monitoring, with the product kept intact.

  • AI-Native Staff Augmentation

    For the stretch between launch and a team of your own: a monthly retainer that keeps the factory on your product for upkeep, maintenance and small features while you hire a full-time CTO or engineers, then hands over to them.

Get a written estimate from your spec

Tell us what you are building and where it is today. We reply within a few business days with questions, or with a scope and a price.