--- title: 'Engineer at Strange Loop Labs' canonical: 'https://feeny.ai/job/engineer-strange-loop-labs-united-states-trj9p63m5nsq' type: 'job' last_seen: '2026-09-09' --- # Engineer at Strange Loop Labs - **Company:** Strange Loop Labs - **Location:** United States - **Employment:** full-time - **Work type:** remote - **Posted:** 2025-01-22 - **Last confirmed live:** 2026-09-09 - **Apply:** https://jobs.ashbyhq.com/strange-loop-labs/dcbfaff8-fd8b-407c-8718-9868d7693206 ## Job description Strange Loop https://www.strangelooplabs.ai automates operations at the world’s largest financial institutions with specialized AI agents. We are a team of engineers (and only engineers) who own both the customer relationship and product end-to-end. Our goal is to remove as many layers as possible between the customer, the engineer, and the product. We don’t have salespeople, product managers, or layers of management, nor do we divide engineers into platform/ML/FDE silos. Our average week involves: - Mastering our customers’ processes as well as their associates - Building AI agents that automate it - Carrying what we learn in the field back into a robust, scalable cloud platform This model is not right for many exceptional engineers, nor should most companies adopt it. But if this sounds like the kind of company you want to build, we’d love to hear from you. In addition to your resume, please include a 1-2 page essay as a cover letter on which principle from the essays below resonates most deeply with you, and provide at least one example from your career of when you have applied that principle (or a time when you wished you had applied it): Our Company Principles As focused as we are on building great solutions for our customers, we are just as focused on building a great company. We have learnt from the good, the bad, and the ugly that our industry has to offer, and are using this to create the company we always wanted to work for. Stay small As anyone who has worked at a large organization knows, keeping hundreds or thousands of people aligned, communicating, and working effectively is difficult, if not impossible. More people, more problems. At Strange Loop, we choose to stay small. This means everyone knows each other, is aligned on strategy, and can re-use the cool stuff others have built. We are energized by figuring out how to get more out of our small team. No middle Staying small requires us to remove a lot of the waste that exists at larger companies. One of those things is the expansive tier of project, product, and middle managers required to keep the behemoth running. At Strange Loop, Engineers speak directly with customers. This enables them to build better products and work around deadlines. Engineers feel the pain of their users, and the relief when they solve it. Remote first Talented people deserve to work where they want. They will not do better work if they live in a particular part of the world, or with a manager looking over their shoulder. Remote work introduces a number of challenges, just as in-office does. We are committed to continually finding better ways of solving them. Share the wealth At Strange Loop, every employee receives salary and equity. We want employees to benefit if we do exit, but we don't want an exit to become the goal. Good companies focus on solving customer problems long-term, not optimizing revenue short-term. To facilitate this, we share the profits we make with all our employees annually. Everyone receives an equal share. This means everyone benefits from the good work they do, and is incentivized to build a better company for the long-term. Our Engineering Principles These are a set of principles that guide how we build software at Strange Loop. You will see examples of these all throughout our codebase, and in the way we work with customers. We reserve the right to change them as we find better ways of working. Always Be Learning Software and customers are changing constantly, as technologies improve and markets change. Therefore, the only sustainable competitive advantage is the ability to learn. We continually discover better ways to leverage technology and serve customers. We also continually learn about how our customers work and the challenges they face, so that we can build them better solutions. Build Quality In We define a high-quality product as one that works the way customers expect it to and is easy to modify in the future. Adding quality in after a product has been released can be difficult: customers will be using it and finding bugs, which creates support load that steals time away from everything else. Therefore, we build quality in from the start, even if doing so means that a feature takes a little longer to build. The time is paid back quickly. Always Be Shipping When we’re building a product, we make a long list of assumptions about how we think customers will use it. Naturally, some of those assumptions are wrong, but we only find out which ones when our product is in the hands of real customers. We therefore try to ship small increments of a product sooner to customers, and seek their feedback as quickly as possible. Make Incremental Improvements Our products are never perfect. There is an infinite list of features we could add, and bugs we could fix, and latencies we could optimize to make them better. Unfortunately, though, we don’t have an infinite amount of time to do them all! Occasionally we will schedule time to make a large improvement, but most of the time we focus on making small, incremental improvements as we go. These small improvements compound over time: each one makes the system easier to develop and operate, which frees up more time, which allows more improvements to be made. Fail Better Next Time We will fail sometimes. Our services will go down, or our accuracy will be poor, or our features will be too difficult to use. This is a natural part of product development. When it happens, no blame will be apportioned, because everyone involved was already trying to do their best. Instead, in these moments of failure, our focus is on what we can gain from it. We dissect what went wrong, possibly come up with some action items, but above all else learn. Create Leverage We deeply embed our engineers with customers, so that we can understand their problems inside and out. Unlike a consulting firm though, we have no intention of hiring thousands of engineers to scale. This means we find ways to create more with less. We do this by building levers into every system we touch so that we can move mountains. Think About The System The success of our company is the result of a large, interconnected, network of “things”. There are customers, and engineers, and a CEO, and a CTO, and services, and databases, and machine-learned models, and public clouds, and many more things. All of these interact in unpredictable ways to create a complex system. When we’re doing our work, though, we only operate on one tiny part at a time. This makes it hard to see the forest for the trees. When making decisions, we do our best to think at the level of the system, and do things that will benefit it as a whole. ## About Strange Loop Labs ## Company Overview - **One-liner**: Strange Loop Labs builds custom, enterprise-grade AI automation products for Fortune 500s, Big Four tax firms, and large asset managers, handling design, build, and ongoing support. - **Entity Type**: Private (backed by top AI investors) - **Headquarters**: Not publicly available (operates as a remote-first company) - **Founded**: Not publicly available - **Founders**: Andrew Stahlman (CEO), Adam Harwood (CTO), Rick Bhardwaj (Director of Engineering) ## Core Business - **Primary industry**: Enterprise AI Automation / Custom AI Software Development - **Target customers**: Fortune 500 companies, Big Four accounting firms, large asset managers (B2B Enterprise) - **Mission or purpose**: To build custom AI products that seamlessly fit into existing enterprise workflows, delivering precision-fit automation with enterprise-grade support and security. ## Products & Services - **Custom AI Platform**: A bespoke, enterprise-grade AI automation platform designed and built by a team of former Amazon Alexa engineers. The platform connects to existing tools (Outlook, SharePoint), processes tens of thousands of documents (PDFs, scans, .xls) in minutes, and is SOC-2 compliant. - **Custom Tax AI**: A specific application automating the processing of complex K-1 tax forms, delivering projected annual cost savings of $9 million and saving thousands of hours of manual work for a large public accounting firm. - **Value-Based Pricing**: Average 2-month ROI on engagements, with continuous model fine-tuning on client data to achieve better-than-human accuracy. ## Market Standing - **Valuation/Market Cap**: Not publicly available - **Key Metric**: Not publicly available (private company) - **Notable Investors/Partners**: Backed by "top AI investors" (specific names not disclosed on the website) - **Growth Signals**: Trusted by Fortune 500s, Big Four tax firms, and large asset managers. Team composed of engineers from the original Amazon Alexa team. Demonstrates strong traction with a case study showing $9M in projected annual cost savings for a single client. ## Competitive Advantages - **Full Lifecycle Ownership**: Unlike consultants who build decks or dev shops that disappear after delivery, Strange Loop handles design, build, and ongoing support, security, and compliance with zero engineering lift from the client. - **Precision-Fit AI**: Works directly alongside client teams to deeply understand workflows, knowledge, and bottlenecks before building, ensuring seamless integration into existing tools. - **Elite Engineering Team**: Founded by engineers from the original Amazon Alexa team, with a focus on world-class AI engineering and continuous model fine-tuning. - **Profit Sharing Model**: All employees receive salary, equity, and an equal share of annual profits, aligning everyone with long-term customer success rather than short-term revenue. ## Strategic Focus - **Stay Small & Efficient**: The company deliberately chooses to remain small to maintain alignment, communication, and effectiveness, focusing on getting more out of a small team rather than scaling headcount. - **Remote-First, No Middle Management**: Engineers speak directly with customers, removing layers of project and product managers to enable faster, better product development. - **Continuous Improvement**: Committed to finding better ways of solving the challenges of remote work and company building, rejecting inertia in favor of constant adaptation. ## Why Work Here - **Culture of Ownership**: Every employee receives salary, equity, and an equal share of annual profits. The company is focused on solving customer problems long-term, not optimizing short-term revenue. - **Remote-First**: Talented people can work where they want. The company is committed to continually finding better ways to solve remote work challenges. - **Small Team, High Impact**: Staying small means everyone knows each other, is aligned on strategy, and can reuse cool stuff others have built. No middle management—engineers speak directly with customers. - **Engineering-Centric**: Engineers feel the pain of their users and the relief when they solve it. The company is built by and for world-class AI engineers. - **Meaningful Work**: Projects include automating complex tax forms for Big Four firms, with demonstrable multi-million dollar impact. ## Sources 1. [strangelooplabs.ai](https://www.strangelooplabs.ai/) 2. [strangelooplabs.ai/careers](https://www.strangelooplabs.ai/careers) 3. [strangelooplabs.ai/about](https://www.strangelooplabs.ai/about) 4. [strangelooplabs.ai/our-company](https://www.strangelooplabs.ai/our-company) 5. 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