Lead Software Development Engineer

At Amperity, we’re an AI-first company helping the world’s leading brands create personalized customer experiences that build loyalty and fuel growth. Our AI-powered Customer Data Cloud, built on multi-patented technology, enables more than 400 global brands, including Alaska Airlines, Wyndham Hotels & Resorts, and DICK’S Sporting Goods, to turn customer data into a competitive advantage.

We unlock the full value of customer data with simplicity and speed. AI is at the core of our platform and the way we work — from powering advanced identity resolution and predictive analytics to streamlining internal workflows and decision-making. It’s not just a capability; it’s part of our DNA.

Our team thrives on curiosity, collaboration, and transparency, fostering a culture where everyone can contribute, learn, and grow. We welcome talented individuals from diverse backgrounds to help us remove data bottlenecks, accelerate business impact, and push the boundaries of what AI can do for the world’s most innovative companies.

With offices in Seattle, New York City, London, and Melbourne, you’ll join a fast-growing team tackling critical challenges at the intersection of AI, data, and customer experience. Ready to make an impact? Let’s talk.

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

We're solving tough problems at the intersection of large-scale data, AI, and user experience. Some of the challenges you will work on include:

• 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 architectures, or cloud-native infrastructure.
• A genuine partner to Product in roadmap planning which translates engineering realities into clear options. This partner also advocates for the right technical investments and helps shape a forward-looking plan. The plan maps what we build to where the business is going.

Technologies We Use

We don't expect you to have experience with everything we use, but if you're excited about learning, you'll do great here. Our tech stack includes:

• Large-scale data engines like Apache Spark, Presto, and Kafka.
• Functional programming languages including Clojure.
• Infrastructure built with Kubernetes and Terraform, deployed across AWS and Azure.
• Native integrations with customer data platforms including Snowflake and Databricks, supporting bring-your-own-storage architectures.
• Machine learning models and systems including random forests, logistic regression, and probabilistic databases.

Location

Seattle, WA

Our hybrid work model includes three days in the office each week, providing a mix of in-person collaboration and remote flexibility

Compensation

Base Salary: $190,000-$260,000. Individual compensation within this range will depend on several factors, including your skills, experience, education/training, geographic location and the level at which you join. We also consider internal equity, market conditions, and overall business needs.

Cash Incentives: Cash incentives are also available.