Associate Customer Success Manager

EasyLlama is transforming the HR compliance industry by reinventing outdated and uninspiring training solutions and adapting them for the mobile-first generation. Our engaging, fun, and interactive training helps millions of employees worldwide build a safer, more positive, and inclusive workplace. As we continue to set the standard in compliance solutions, our vision extends far beyond training—we aim to partner with thousands of organizations to reduce employee risk and foster a more inclusive and secure environment for all.

With world-class customer reviews—boasting a 96% rating on G2 from over 100 reviews—and industry-leading NPS and Customer Satisfaction scores, EasyLlama is proud to have earned the trust of over 5,000 clients, including brands like Shake Shack, WeightWatchers, Sephora, JiffyLube, and Y Combinator. Our mobile-friendly platform delivers on-demand, self-paced, and bite-sized solutions that meet employees where they are, increasing engagement and retention.

At EasyLlama, we are not just transforming compliance training—we are challenging the status quo. We have a strong culture of collaboration, innovation, and getting things done.

Our CORE values

DRIVE is how we work at EasyLlama. Weʼre Doers, Resourceful,
Impactful, Valued Partners, & Excellence-Focused.

• We are Doers. We proactively make things happen.

• We are Resourceful. We treat time, money, and energy as valuable.

• We are Impactful. We prioritize what matters.

• We are Valued Partners. We put customers & teammates first.

• We are Excellence-Obsessed. We always deliver excellent work.

From CEO to newest hire, DRIVE asks us to take ownership, solve
problems, prioritize what matters, support teammates, and deliver high-
quality work.

When we live these values, our product choices, customer interactions,
hiring, and promotions all help us live out our mission: to build safer and
more productive workplaces.

About the Role

We’re hiring an Associate Customer Success Manager to own our tech touch (low-ARR) customer segment.

This segment is primarily driven by automation, but when customers reach out, you’re the human behind the experience. You’ll manage inbound inquiries, resolve issues quickly, and ensure customers feel supported in a high-volume, systems-driven environment.

This is a high-ownership IC role. You’ll be responsible for delivering a consistent, high-quality customer experience at scale while operating with speed, precision, and strong attention to detail.

What You’ll Do

• Own all inbound customer inquiries for the scaled segment (email, chat, support tickets)

• Respond quickly and effectively to:

  • Product questions

  • Basic troubleshooting

  • Account and billing requests

  • Process Upgrades

• Triage and escalate more complex issues to Support, Product, or Engineering

• Ensure nothing slips through the cracks across a high volume of requests

• Maintain clean, accurate data across CRM and support tools

• Identify patterns in inbound requests and drive improvements to:

  • Help center content

  • Macros and templates

  • Automated workflows

• Partner cross-functionally to improve the efficiency and quality of the scaled customer experience

• Help build our scaled Customer Success motion

Who You Are

• 1–3 years in Customer Success, Support, or another customer-facing role

• Strong written communication — clear, concise, and friendly

• Highly organized with strong attention to detail

• Ability to manage high volume with speed and accuracy

• Systems-oriented — comfortable working within and improving structured processes

• Resourceful and proactive — you look for patterns and solve problems, not just respond to them
  

Nice to Have

• Experience supporting a scaled or high-volume customer segment

• Familiarity with tools like HubSpot, Front, or similar

• Experience working in a SaaS environment

What Success Looks Like

• Customers receive fast, accurate, and helpful responses

• Inbound volume is managed efficiently with strong SLAs and minimal backlog

• Common issues are identified and reduced over time

• The scaled segment feels supported, even in a primarily automated model