Lead Software Development Engineer

WeHireYou; Seattle (WA); On-site; USD 180,000 - 260,000; Full time

Job summary

Amperity is seeking a Lead Software Development Engineer to help advance Loom, unifying batch and real-time processing and scaling a high-ownership platform used by industry-leading brands. You will drive architecture, manage a large codebase, and guide how to prioritize technical debt and investments.

You will advance AI-forward practices, deliver measurable value, and work closely with product and platform teams.

Qualifications

• 9+ years building and evolving complex, high-scale software systems.
• Experience leading platform migrations or major architectural transitions.
• Fluent in AI tooling capabilities and guiding teams to apply them safely.

Responsibilities

• Unify batch and real-time event processing across core platform services.
• Manage a large, mature codebase and plan which tech debt to carry, pay down, or eliminate.
• Translate customer and business requirements into high-value engineering work.
• Build seamless integrations with data platforms and cloud infrastructure.
• Raise the team's AI velocity by establishing clear norms for AI tooling use.

Skills

Senior engineer

Platform migrations

Distributed systems

AI tooling

Codebase management

Job description

Lead Software Development Engineer

About Amperity—Why This, Why Now

Most customer data is a lie by omission.

Every consumer brand wants to know its customers. Unfortunately, almost none actually do. Data is scattered across a dozen systems, half of it contradicts the other half, and \"insights\" teams are forced to act on incomplete guesses. We started Amperity ten years ago because that gap—between what a brand believes about its customers and what is true— is the most expensive problem in the industry, and nobody had solved it.

With a lot of hard work and a little bit of luck, we did. Our patented identity resolution takes billions of messy, conflicting records and resolves them into an accurate picture of a real human being—in hours, not months. That’s not a feature; it’s the foundation everything else stands on. It’s why more than 400 brands—like Alaska Airlines, Wyndham Hotels & Resorts, DICK’S Sporting Goods, Virgin Atlantic, and Brooks Running—trust us with the one thing they can’t afford to get wrong, and why IDC named us a Leader in the category in 2026.

Now we’re doing something harder. We’re rebuilding Amperity as an AI-first company—not bolting a chatbot onto old software, but putting agents at the center of how customer data actually gets used. We shipped the industry’s first identity resolution agent, then the first enterprise Customer Data Agent that turns a plain-language question into a live segment without waiting on an engineering queue. The bet underneath all of it is simple, and we think it’s correct: The potential of AI will not be realized for a brand until it’s grounded and activated against a true, unified view of the customer. The market at-large is focused on intelligence, and we are focused on being the ones who can make it trustworthy.

So here’s the honest pitch. If you want a tour of a category that’s already been figured out, this isn’t it. If you want to help decide what the next version of an entire industry looks like—alongside people who are remarkably exceptional at what they do, solving a problem that requires deep, sustained focus—this is one of the few places that work exists. Our goal is to build a highly impactful, generational business.

We measure our success by one standard: whether what we build moves the business. Return on cognition, not return on hype. If that’s how you want to be measured, we would love to speak with you.

The Team

You’ll join Loom, the largest team at Amperity and the one at the heart of the platform. Loom owns the primary services that define what Amperity is: identity resolution, real-time customer profiles, streaming data ingestion, and the foundational libraries that the engineering department builds on. If Amperity is an operating system for customer data, Loom is the kernel.

Over the last year, the Loom team has built out the first version of the real-time stream processing to accompany the battle-hardened core batch processing system. In your first year, the highest-priority goal is to help the teams apply the lessons learned thoughtfully to the broader platform. This is not a greenfield rewrite. It is the more interesting and more demanding challenge of evolving a large platform, without breaking what our customers depend on.

Loom operates with a large surface area and the work matters directly to customers. We expect our engineers to be AI-forward, using AI tooling to remove barriers and bringing clear judgment about where it can and cannot move the needle. You will report to the Senior Manager, Loom.

Interesting Problems

• You will lead the effort to unify batch and real-time event processing across core platform services.


• You will manage a large, mature codebase and develop a clear strategy for which technical debt to carry, which to pay down, and which to eliminate.


• Translate customer requirements into well-scoped, high-value engineering work, knowing when to apply solutions and when the problem is unique enough to warrant deeper investment.


• Building seamless integrations with the data platforms and cloud infrastructure our customers already operate in.


• Raising the team’s AI velocity requires establishing clear norms. These norms define where AI tooling accelerates delivery, where it misleads, and how to validate what it produces. By doing so, every engineer works faster and more effortlessly with it.

About You

You know how to operate in a complex, high-ownership environment. You don’t need everything to be greenfield. You excel when you can assess a system honestly, identify what’s holding the team back, and build a credible path forward.

• 9+ years building and evolving complex, high-scale software systems.


• Experience leading platform migrations or major architectural transitions (streaming experience a strong plus).


• You can distinguish between problems that have well-trodden solutions from those that are genuinely unique, and the discipline to apply the former quickly so the team can focus on the latter.


• Fluent in the capabilities of AI tooling, while balancing its limitations. You also help raise the AI fluency of the engineers around you through different means, including pairing, design reviews, and setting a high bar for where and how it gets applied.


• A track record of fast value delivery: shipping high-quality work, iterating based on evidence, and making confident decisions through ambiguity.


• Comfortable inheriting large, imperfect codebases. You can read technical debt, communicate it with partners, and make principled calls about when to sustain it and when to address it.


• Customer-first thinking where you start with the value you deliver, not the implementation, and that shapes how you scope and sequence work.

Technical depth in distributed systems, data-intensive...