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4 min read

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Mar 4, 2025

Inbox chimes… It was March 2021, and I had just received an email about an Implementation Engineering Manager role at a startup. After reading the job description, chatting with the team, interviewing, and ultimately accepting the position, I knew one thing for sure — there wasn’t going to be a blueprint. But there was a vision, and that would be my guiding light.

This role was critical in bridging the gap between customers, a non-technical customer support team, and a non-client-facing engineering team. The biggest initial challenges? A lack of processes, unclear escalation paths, and a growing backlog of product and engineering tasks.

Coming from a Senior API Support Engineer Team Lead role, I knew what it would take to nurture the team technically. But learning how to build a high-performing support engineering team from scratch? That was a whole new challenge — and I had to do it fast.

My first three months were all about learning the business, stepping into the role of the first Support Engineer to get hands-on experience, creating an escalation path, and — most importantly — making my first hire before peak season (Q4).

The early days were a crash course in product knowledge, customer needs, and internal workflows. I spent time with key stakeholders, documented processes, and studied what success would look like for my team. Once I had a solid understanding, I kicked off the recruiting and interview process.

It became clear early on that the ideal Support Engineer would need a mix of technical expertise, collaboration skills, and strong communication abilities. Unlike traditional engineering roles, these hires needed to translate technical issues for a wide range of audiences — not just developers. Finding this balance in candidates was key to setting the team up for success.

The best way to build scalable processes? Start with experience, not assumptions.

In the early days, I had to create clear workflows for: ✅ Client escalations ✅ Bug tracking and feature requests ✅ Internal handoffs between Support, Engineering, and Product ✅ Reporting and data collection

But documentation alone wasn’t enough — it needed to be useful.

Our external Help Center wasn’t just for customers — it became a resource for internal teams, reducing the number of repetitive support tickets.

Our internal knowledge base (separate from customer-facing docs) became the go-to hub for internal processes, SOPs, and troubleshooting guides.

Automations and integrations played a huge role in streamlining workflows — especially within Zendesk, Jira, and Slack.

One key lesson? Don’t overcomplicate things too quickly. Rolling out new processes without buy-in can backfire. Gradual implementation, backed by team feedback, made adoption smoother.

One of the biggest hurdles? Getting Engineering to prioritize customer issues effectively.

Prioritization is an art, not just a science. While on-call rotations kept engineers engaged in issue resolution, there needed to be clear benchmarks for determining priority levels.

That’s where the Support Engineering team came in. We provided real-time insights on issue impact — helping Engineering understand why a particular bug needed urgent attention.

A frequent challenge was the fine line between: ❌ “This is a support issue.” ❌ “This is a product gap.”

Advocating for a balance between short-term fixes and long-term solutions became critical. Support and Engineering couldn’t operate in silos — we had to work together to create real customer impact.

Leadership wanted KPIs, but I quickly realized something: pulling data from Slack, Stack Overflow, and Google Drive wasn’t going to cut it.

We needed collaborative tools like: ✅ Zendesk (for tracking contact reason codes, SLAs, CSAT, and internal collaboration) ✅ Jira (for bug tracking and feature requests) ✅ Confluence (for process documentation and SOPs)

Before switching to Jira and Confluence, we used Monday.com and Stack Overflow. These tools worked at first, but as we scaled, we needed robust reporting and collaboration tools to track trends and advocate for resources.

One surprising takeaway? I stopped focusing on contacts per order. While it seemed like an important metric, it didn’t drive meaningful improvements. Tracking contact reason code trends, on the other hand, helped us get ahead of recurring customer pain points.

If I had to do this again, what would I do differently?

👉 Prioritize relationship-building across departments. Your team’s value isn’t just for customers — it benefits Engineering, Product, Sales, and beyond. Understanding this earlier would have helped me advocate for my team even more effectively.

👉 Don’t wait for perfection before launching processes. Iterate as you go. A “good enough” process that exists is better than the perfect process that never gets implemented.

👉 Cross-functional collaboration isn’t just important — it’s essential. Support Engineering isn’t just a customer-facing team. It’s a strategic partner in improving product quality, reducing churn, and driving innovation.

Yes, Support Engineering is about troubleshooting, debugging, and de-escalating client issues.

But it’s also about: ✅ Driving product improvements ✅ Reducing customer churn ✅ Building trust through proactive support

I truly loved building a Support Engineering team from scratch. It reinforced my belief that support teams deserve a bigger seat at the table — not just as problem solvers, but as key contributors to business success.

💬 Have you built a support team from scratch? What lessons did you learn? Let’s discuss!