About the job
About Hightouch
Hightouch is an innovative AI platform tailored for marketing and growth teams. Our cutting-edge AI agents transform marketing workflows, enabling marketers to efficiently craft content, strategize campaigns, and implement strategies with exceptional speed and effectiveness.
Situated at the forefront of two pivotal technological advancements—progress in large language models (LLMs) and agentic AI, alongside the swift adoption of cloud data warehouses like Snowflake and Databricks—Hightouch has emerged as a leader in AI-driven marketing. We proudly collaborate with industry giants such as Domino’s, Chime, Spotify, Ramp, Whoop, Grammarly, and over 1000 others.
Our dedicated team is committed to delivering impactful solutions for our clients. We embrace challenges with analytical thinking, prioritize agility, and foster a culture of compassion and support. We seek team members who excel in communication, possess a growth-oriented mindset, and are driven to achieve our collective objectives.
The Customer Challenge
When you access platforms like Spotify, each user experiences a unique homepage. Similarly, Nike personalizes product rankings based on user preferences, and Chase tailors offers to individual spending habits. This is the essence of web and mobile personalization: dynamically determining what each customer engages with in real-time, directly influencing conversion rates, customer retention, and revenue at critical moments of user interaction.
Despite the evident benefits, few organizations excel in this area outside of those developing custom solutions. For instance, a single experiment aimed at assessing whether high-spending users respond more favorably to a loyalty upsell requires a collaborative effort involving analysts, product managers, designers, engineers, and data monitors. Most teams conduct only 5–10 experiments each quarter, often relying on a limited set of static rules that apply to just a fraction of their user base.
Existing tools, such as Optimizely, Dynamic Yield, and Adobe Target, address infrastructure needs but fail to resolve the coordination challenges inherent in personalization. Each experiment, audience, and content piece necessitates manual configuration, and many companies find themselves duplicating customer data into proprietary systems, leading to prolonged implementation times and vendor lock-in.
Why Agentic AI is the Future
The transition from