About Hightouch

Hightouch’s mission is to empower everyone to take action on their data. Through our Reverse ETL platform, business and data users can seamlessly sync data from where it resides, such as warehouses and databases, to where it is needed, including operational systems and SaaS tools. Traditionally, acting on data has required engineering time and bandwidth, and left most business users stuck with charts and reports that are unable to take automated action on their data. With Hightouch, every business user, without writing any code, can activate data to streamline critical processes, improve marketing performance, and scale operations.

Our team operates with a focus on making a meaningful impact for our customers. We believe in approaching challenges with a first principles thinking mindset, moving quickly and embracing our value of efficient execution, and treating each other with compassion and kindness. We look for team members that are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.

Hundreds of companies use Hightouch, including Spotify, Ramp, Grammarly, NBA, Plaid, and Betterment. We’re based in San Francisco, are remote-friendly, and backed by leading investors such as Amplify Partners, ICONIQ Growth, Bain Capital Ventures, Y-Combinator, and Afore Capital.

About the Role

Hightouch's mission has always been to empower customers to harness their data to drive business impact. With the rise of AI and machine learning, we are focused on helping growth teams use the wealth of customer data in their warehouse to make personalized and optimized decisions at a scale far beyond human capabilities.

AI Decisioning enables growth teams to continuously experiment with various creative approaches and strategies, personalize content based on a deep understanding of each customer, and optimize outcomes to drive customers towards the best possible results.

As an early member of our AI Decisioning team, you’ll play an essential role in shaping and scaling our machine learning platform. You will work closely with the CTO and product teams to architect robust, highly performant systems that empower growth teams to automate decision-making. On a typical day, you will be:

• Designing and building scalable backend systems and ML infrastructure to process and analyze vast amounts of data in real-time
• Developing AI-driven features that enable hyper-personalization and decision automation for growth teams
• Working closely with machine learning engineers to experiment with cutting-edge techniques and integrate them into our platform

Looking ahead, AI and machine learning will be the foundation of a new operational paradigm in marketing. AI Decisioning will enable marketers to better understand their users by providing actionable insights and guiding decision-making. Additionally, large language models (LLMs) will offer deep insights into the content being sent out, helping marketers refine their strategies and deliver truly personalized experiences at scale.

We are looking for talented engineers with expertise in backend systems, distributed computing, and a passion for building a product from zero to one. Experience with building ML platforms is helpful, but not required. The salary range for this role is $180,000 - $260,000 USD per year, fully remote and location-independent. We also offer meaningful equity compensation in the form of ISO options, and offer early exercise and a 10 year post-termination exercise window.

 

Interview Process

Our goal with the interview process is to balance speed with giving both parties opportunities to assess whether there is a strong mutual fit. We will ask you questions, but we want you to ask us questions! Our technical interviews focus on how you design systems because we believe this is the best way for us to see how you work and for you to see how we collaborate. We don’t ask you to write code to solve technical brainteasers that don’t appear in your day to day job.

• Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit.
• System Design Screen [45m]: Designing a data processing feature end-to-end.
• Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.
• System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.